MongoDB is the most famous and loved NoSQL database. It has many features that are easy to handle when compared to conventional RDBMS. These slides contain the basics of MongoDB.
In this presentation, Raghavendra BM of Valuebound has discussed the basics of MongoDB - an open-source document database and leading NoSQL database.
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The document provides an introduction and overview of MongoDB, including what NoSQL is, the different types of NoSQL databases, when to use MongoDB, its key features like scalability and flexibility, how to install and use basic commands like creating databases and collections, and references for further learning.
The document discusses MongoDB concepts including:
- MongoDB uses a document-oriented data model with dynamic schemas and supports embedding and linking of related data.
- Replication allows for high availability and data redundancy across multiple nodes.
- Sharding provides horizontal scalability by distributing data across nodes in a cluster.
- MongoDB supports both eventual and immediate consistency models.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
This document provides an overview and introduction to MongoDB, an open-source, high-performance NoSQL database. It outlines MongoDB's features like document-oriented storage, replication, sharding, and CRUD operations. It also discusses MongoDB's data model, comparisons to relational databases, and common use cases. The document concludes that MongoDB is well-suited for applications like content management, inventory management, game development, social media storage, and sensor data databases due to its flexible schema, distributed deployment, and low latency.
MongoDB is a document-oriented NoSQL database written in C++. It uses a document data model and stores data in BSON format, which is a binary form of JSON that is lightweight, traversable, and efficient. MongoDB is schema-less, supports replication and high availability, auto-sharding for scaling, and rich queries. It is suitable for big data, content management, mobile and social applications, and user data management.
MongoDB is an open-source, document-oriented database that provides flexible schemas, horizontal scaling, and high performance. It stores data as JSON-like documents with dynamic schemas, making the integration of data easier for developers. MongoDB can be scaled horizontally and supports replication and load balancing for high availability.
The document is a slide presentation on MongoDB that introduces the topic and provides an overview. It defines MongoDB as a document-oriented, open source database that provides high performance, high availability, and easy scalability. It also discusses MongoDB's use for big data applications, how it is non-relational and stores data as JSON-like documents in collections without a defined schema. The presentation provides steps for installing MongoDB and describes some basic concepts like databases, collections, documents and commands.
This document provides an overview and introduction to MongoDB. It discusses how new types of applications, data, volumes, development methods and architectures necessitated new database technologies like NoSQL. It then defines MongoDB and describes its features, including using documents to store data, dynamic schemas, querying capabilities, indexing, auto-sharding for scalability, replication for availability, and using memory for performance. Use cases are presented for companies like Foursquare and Craigslist that have migrated large volumes of data and traffic to MongoDB to gain benefits like flexibility, scalability, availability and ease of use over traditional relational database systems.
This document provides an introduction to NoSQL and MongoDB. It discusses that NoSQL is a non-relational database management system that avoids joins and is easy to scale. It then summarizes the different flavors of NoSQL including key-value stores, graphs, BigTable, and document stores. The remainder of the document focuses on MongoDB, describing its structure, how to perform inserts and searches, features like map-reduce and replication. It concludes by encouraging the reader to try MongoDB themselves.
MongoDB is a non-relational database that stores data in JSON-like documents with dynamic schemas. It features flexibility with JSON documents that map to programming languages, power through indexing and queries, and horizontal scaling. The document explains that MongoDB uses JSON and BSON formats to store data, has no fixed schema so fields can evolve freely, and demonstrates working with the mongo shell and RoboMongo GUI.
MongoDB is a cross-platform document-oriented database system that is classified as a NoSQL database. It avoids the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas. MongoDB was first developed in 2007 and is now the most popular NoSQL database system. It uses collections rather than tables and documents rather than rows. Documents can contain nested objects and arrays. MongoDB supports querying, indexing, and more. Queries use JSON-like documents and operators to specify search conditions. Documents can be inserted, updated, and deleted using various update operators.
MongoDB is an open-source, document-oriented database that provides high performance and horizontal scalability. It uses a document-model where data is organized in flexible, JSON-like documents rather than rigidly defined rows and tables. Documents can contain multiple types of nested objects and arrays. MongoDB is best suited for applications that need to store large amounts of unstructured or semi-structured data and benefit from horizontal scalability and high performance.
Mongo DB: Fundamentals & Basics/ An Overview of MongoDB/ Mongo DB tutorialsSpringPeople
The document discusses MongoDB, an open-source document database. It provides an overview of MongoDB, including what it is, why it is used, its basic concepts like databases, collections, and documents, and how it compares to a relational database. It also covers MongoDB commands for creating and dropping collections, inserting, querying, and updating documents.
Slidedeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.
The document introduces MongoDB as a scalable, high-performance, open source, schema-free, document-oriented database. It discusses MongoDB's philosophy of flexibility and scalability over relational semantics. The main features covered are document storage, querying, indexing, replication, MapReduce and auto-sharding. Concepts like collections, documents and cursors are mapped to relational database terms. Examples uses include data warehousing and debugging.
This document provides an overview of MongoDB, a document-oriented NoSQL database. It discusses how MongoDB can efficiently store and process large amounts of data from companies like Walmart, Facebook, and Twitter. It also describes some of the problems with relational databases and how MongoDB addresses them through its flexible document model and scalable architecture. Key features of MongoDB discussed include storing data as JSON-like documents, dynamic schemas, load balancing across multiple servers, and its CRUD operations for creating, reading, updating, and deleting documents.
- MongoDB is an open-source, high-performance, schema-free, document-oriented database. It bridges the gap between key-value stores and traditional relational databases.
- Documents in MongoDB are like JSON documents and can be dynamically updated without migrations. MongoDB supports aggregation, map-reduce functions, and rich queries.
- PyMongo is the Python driver for MongoDB. Documents can be easily inserted, queried, and manipulated from Python. Object-document mappers like MongoEngine allow defining schemas and models similarly to ORMs.
This document provides an overview of NoSQL databases and compares them to relational databases. It discusses the different types of NoSQL databases including key-value stores, document databases, wide column stores, and graph databases. It also covers some common concepts like eventual consistency, CAP theorem, and MapReduce. While NoSQL databases provide better scalability for massive datasets, relational databases offer more mature tools and strong consistency models.
This document introduces HBase, an open-source, non-relational, distributed database modeled after Google's BigTable. It describes what HBase is, how it can be used, and when it is applicable. Key points include that HBase stores data in columns and rows accessed by row keys, integrates with Hadoop for MapReduce jobs, and is well-suited for large datasets, fast random access, and write-heavy applications. Common use cases involve log analytics, real-time analytics, and messages-centered systems.
Introduction to MongoDB and CRUD operationsAnand Kumar
Learn about MongoDB basics, its advantages, history.
Learn about the installation of MongoDB.
Learn Basics of create,insert,update,delete documents in MongoDB.
Learn basics of NoSQL.
This is the presentation I made on JavaDay Kiev 2015 regarding the architecture of Apache Spark. It covers the memory model, the shuffle implementations, data frames and some other high-level staff and can be used as an introduction to Apache Spark
Basic of Mongodb With the description of NoSQl database and its features about colleactions and documents.Its advantages and disadvantages.Why to use MongoDB.Difference between RDBMS and MongoDB.Installation process of MongoDB.Varoius BSON Types.Keypoints Of MongoDB.
Keywords:NOSQL,BSON Types,Replication,Sharding,Aggregations,ObjectId and various others.
1> Why Choose NoSQL
2> MongoDB -NoSQL Database
3> MongoDB BioGraphy
4> RDBMS VS MongoDB
5> Query Language in MYSQL Vs MongoDB
6> Key Features
7> MongoDB Basics
8> MongoDB Collections
9> MongoDB Aggregations
10> Aggregation Pipeline
11> Single Purpose Aggregation Operations
12> MongoDB Replication
13> Sharding in MongoDB
14> Pros / Cons Of MongoDB
15> Why should use MongoDB
17> Where should use MongoDB?
Conclusion:MongoDB database is used to store big data.It gives high performance and scalability features which makes advanced in terms of SQL database
MongoDB is a document-oriented NoSQL database written in C++. It uses a document data model and stores data in BSON format, which is a binary form of JSON that is lightweight, traversable, and efficient. MongoDB is schema-less, supports replication and high availability, auto-sharding for scaling, and rich queries. It is suitable for big data, content management, mobile and social applications, and user data management.
MongoDB is an open-source, document-oriented database that provides flexible schemas, horizontal scaling, and high performance. It stores data as JSON-like documents with dynamic schemas, making the integration of data easier for developers. MongoDB can be scaled horizontally and supports replication and load balancing for high availability.
The document is a slide presentation on MongoDB that introduces the topic and provides an overview. It defines MongoDB as a document-oriented, open source database that provides high performance, high availability, and easy scalability. It also discusses MongoDB's use for big data applications, how it is non-relational and stores data as JSON-like documents in collections without a defined schema. The presentation provides steps for installing MongoDB and describes some basic concepts like databases, collections, documents and commands.
This document provides an overview and introduction to MongoDB. It discusses how new types of applications, data, volumes, development methods and architectures necessitated new database technologies like NoSQL. It then defines MongoDB and describes its features, including using documents to store data, dynamic schemas, querying capabilities, indexing, auto-sharding for scalability, replication for availability, and using memory for performance. Use cases are presented for companies like Foursquare and Craigslist that have migrated large volumes of data and traffic to MongoDB to gain benefits like flexibility, scalability, availability and ease of use over traditional relational database systems.
This document provides an introduction to NoSQL and MongoDB. It discusses that NoSQL is a non-relational database management system that avoids joins and is easy to scale. It then summarizes the different flavors of NoSQL including key-value stores, graphs, BigTable, and document stores. The remainder of the document focuses on MongoDB, describing its structure, how to perform inserts and searches, features like map-reduce and replication. It concludes by encouraging the reader to try MongoDB themselves.
MongoDB is a non-relational database that stores data in JSON-like documents with dynamic schemas. It features flexibility with JSON documents that map to programming languages, power through indexing and queries, and horizontal scaling. The document explains that MongoDB uses JSON and BSON formats to store data, has no fixed schema so fields can evolve freely, and demonstrates working with the mongo shell and RoboMongo GUI.
MongoDB is a cross-platform document-oriented database system that is classified as a NoSQL database. It avoids the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas. MongoDB was first developed in 2007 and is now the most popular NoSQL database system. It uses collections rather than tables and documents rather than rows. Documents can contain nested objects and arrays. MongoDB supports querying, indexing, and more. Queries use JSON-like documents and operators to specify search conditions. Documents can be inserted, updated, and deleted using various update operators.
MongoDB is an open-source, document-oriented database that provides high performance and horizontal scalability. It uses a document-model where data is organized in flexible, JSON-like documents rather than rigidly defined rows and tables. Documents can contain multiple types of nested objects and arrays. MongoDB is best suited for applications that need to store large amounts of unstructured or semi-structured data and benefit from horizontal scalability and high performance.
Mongo DB: Fundamentals & Basics/ An Overview of MongoDB/ Mongo DB tutorialsSpringPeople
The document discusses MongoDB, an open-source document database. It provides an overview of MongoDB, including what it is, why it is used, its basic concepts like databases, collections, and documents, and how it compares to a relational database. It also covers MongoDB commands for creating and dropping collections, inserting, querying, and updating documents.
Slidedeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.
The document introduces MongoDB as a scalable, high-performance, open source, schema-free, document-oriented database. It discusses MongoDB's philosophy of flexibility and scalability over relational semantics. The main features covered are document storage, querying, indexing, replication, MapReduce and auto-sharding. Concepts like collections, documents and cursors are mapped to relational database terms. Examples uses include data warehousing and debugging.
This document provides an overview of MongoDB, a document-oriented NoSQL database. It discusses how MongoDB can efficiently store and process large amounts of data from companies like Walmart, Facebook, and Twitter. It also describes some of the problems with relational databases and how MongoDB addresses them through its flexible document model and scalable architecture. Key features of MongoDB discussed include storing data as JSON-like documents, dynamic schemas, load balancing across multiple servers, and its CRUD operations for creating, reading, updating, and deleting documents.
- MongoDB is an open-source, high-performance, schema-free, document-oriented database. It bridges the gap between key-value stores and traditional relational databases.
- Documents in MongoDB are like JSON documents and can be dynamically updated without migrations. MongoDB supports aggregation, map-reduce functions, and rich queries.
- PyMongo is the Python driver for MongoDB. Documents can be easily inserted, queried, and manipulated from Python. Object-document mappers like MongoEngine allow defining schemas and models similarly to ORMs.
This document provides an overview of NoSQL databases and compares them to relational databases. It discusses the different types of NoSQL databases including key-value stores, document databases, wide column stores, and graph databases. It also covers some common concepts like eventual consistency, CAP theorem, and MapReduce. While NoSQL databases provide better scalability for massive datasets, relational databases offer more mature tools and strong consistency models.
This document introduces HBase, an open-source, non-relational, distributed database modeled after Google's BigTable. It describes what HBase is, how it can be used, and when it is applicable. Key points include that HBase stores data in columns and rows accessed by row keys, integrates with Hadoop for MapReduce jobs, and is well-suited for large datasets, fast random access, and write-heavy applications. Common use cases involve log analytics, real-time analytics, and messages-centered systems.
Introduction to MongoDB and CRUD operationsAnand Kumar
Learn about MongoDB basics, its advantages, history.
Learn about the installation of MongoDB.
Learn Basics of create,insert,update,delete documents in MongoDB.
Learn basics of NoSQL.
This is the presentation I made on JavaDay Kiev 2015 regarding the architecture of Apache Spark. It covers the memory model, the shuffle implementations, data frames and some other high-level staff and can be used as an introduction to Apache Spark
Basic of Mongodb With the description of NoSQl database and its features about colleactions and documents.Its advantages and disadvantages.Why to use MongoDB.Difference between RDBMS and MongoDB.Installation process of MongoDB.Varoius BSON Types.Keypoints Of MongoDB.
Keywords:NOSQL,BSON Types,Replication,Sharding,Aggregations,ObjectId and various others.
1> Why Choose NoSQL
2> MongoDB -NoSQL Database
3> MongoDB BioGraphy
4> RDBMS VS MongoDB
5> Query Language in MYSQL Vs MongoDB
6> Key Features
7> MongoDB Basics
8> MongoDB Collections
9> MongoDB Aggregations
10> Aggregation Pipeline
11> Single Purpose Aggregation Operations
12> MongoDB Replication
13> Sharding in MongoDB
14> Pros / Cons Of MongoDB
15> Why should use MongoDB
17> Where should use MongoDB?
Conclusion:MongoDB database is used to store big data.It gives high performance and scalability features which makes advanced in terms of SQL database
This document provides an introduction to MongoDB, a non-relational NoSQL database. It discusses what NoSQL databases are and their benefits compared to SQL databases, such as being more scalable and able to handle large, changing datasets. It then describes key features of MongoDB like high performance, rich querying, and horizontal scalability. The document outlines concepts like document structure, collections, and CRUD operations in MongoDB. It also covers topics such as replication, sharding, and installing MongoDB.
This document provides an overview of MongoDB and discusses its installation and configuration on Windows systems. It covers downloading the appropriate MongoDB version, installing the downloaded file, setting up the MongoDB environment by creating a data directory and log files, and connecting to MongoDB using the mongo shell. The document is divided into multiple sections covering MongoDB's features, data modeling using documents, database and collection management operations, and connecting to MongoDB from Java applications.
Sigit Kurniawan discusses MongoDB and provides an overview of key concepts. The document covers SQL vs NoSQL, MongoDB features, data types, installation on Windows, and CRUD operations. MongoDB is a document database designed for scalability and flexible schemas. It uses dynamic schemas and is horizontally scalable.
MongoDB is a scalable high-performance open-source document-orientated database which is built for speed, rich document based queries for easy readability, full index support for high performance, replication and failover for high availability, auto sharding for easy scalability and map/reduce for aggregation.
MongoDB is an open-source, document-oriented, NoSQL database that provides scalability, performance, and high availability. It is written in C++ and stores data in flexible, JSON-like documents, allowing for easy querying and retrieval of data. MongoDB is commonly used for applications that require scalability and large datasets, and provides features like auto-sharding, replication, and rich queries.
Introduction to MongoDB Basics from SQL to NoSQLMayur Patil
This document provides an introduction to databases and MongoDB. It discusses the purpose of databases, types of databases including relational and non-relational, and the relational model. It then focuses on MongoDB, describing its basics like JSON and BSON storage formats, CRUD terms, features around performance, availability and scaling, and some limitations. Popular applications of databases are also listed.
This document provides an overview of MongoDB, including what NoSQL is, different NoSQL database types like document databases, features of MongoDB like its document-based and schemaless structure, when MongoDB would be a good fit like for large datasets with changing schemas, and how to install MongoDB on Windows, Mac, and Ubuntu.
MongoDB is a document database that provides high performance, high availability, and easy scalability through embedding, indexing, replication, and sharding. It uses a dynamic schema which allows polymorphism and flexible data structures. MongoDB stores data as documents with dynamic schema in BSON format and provides CRUD operations through methods like insert(), find(), update(), and remove(). It can be deployed in standalone, replica set, or sharded cluster configurations for scaling.
MongoDB is a high-performance, open-source document database that provides high availability, easy scalability, and uses dynamic schemas. It stores data in flexible, JSON-like documents, meaning fields can vary from document to document and data structure can change over time. MongoDB is commonly used for big data and real-time applications.
https://youtu.be/Fg59YTotccY
Database workshop 2023-02-20
Ido Ben Haim and Daniyal Bokhari on February 20, 2023
Requirement: None
What you’ll learn:
* NoSQL database design (mongodb)
This document provides an overview of MongoDB, including: a brief history of databases from the 1960s to today's NoSQL databases and cloud computing; how MongoDB stores data in databases, collections of documents, and fields; MongoDB's document model for storing data; and basic operations like installation, running the MongoDB shell, saving and retrieving data, replication, and sharding.
MongoDB is a cross-platform document-oriented database program that uses JSON-like documents with dynamic schemas, commonly referred to as a NoSQL database. It allows for embedding of documents and arrays within documents, hierarchical relationships between data, and indexing of data for efficient queries. MongoDB is developed by MongoDB Inc. and commonly used for big data and content management applications due to its scalability and ease of horizontal scaling.
The document discusses the evolution of databases from flat files to relational databases to NoSQL databases like MongoDB. It provides an overview of MongoDB, describing it as a free, open-source, cross-platform, document-oriented database designed for scalability. Some key features of MongoDB are that it uses dynamic schemas, is horizontally scalable, and supports replication and sharding for high availability. The document also compares MongoDB to relational databases and provides examples of CRUD operations and data modeling in MongoDB.
In this workshop we will deploy a pre-built Node website to Heroku, then hook it up to an mLabs MongoDB instance. We will then use both the Mongo Shell and a GUI based app to import and export data, save and modify documents, and run queries. Finally, we'll use our knowledge of Mongo queries to create a RESTful api for the Node app.
This is a workshop designed for experienced JavaScript developers. You must already be familiar with the following: JavaScript, Git, using a programming editor, running commands from the terminal, and launching a web server on your own machine.
Since its first appearance in 2009, NodeJS has come a long way. Many frameworks have been developed on top of it. These all make our task easy and quick. It is us who need to decide which one to choose? So, here is the list of top 10 NodeJS frameworks that will help you build an awesome application.
Salesforce Tutorial for Beginners: Basic Salesforce IntroductionHabileLabs
Salesforce is the worlds best Customer Relationship Management (CRM) platform which is flexible and powerful database supplier in the market.This blog is introducing about Salesforce and it’s CRM, Multitenant Architecture etc.
This document provides an overview of end-to-end testing with Protractor. It defines end-to-end testing as testing whether the flow of an application performs as designed from start to finish. The document then discusses Protractor, an end-to-end test framework for AngularJS, how it works by using WebDriverJS and Selenium, and its advantages like automatic waiting and support for page objects. Finally, the document provides instructions on installing Protractor and a demo of running tests.
It is a purely invented, non-blocking infrastructure to script highly concurrent programs.
Node.js is an open source, cross-platform JavaScript runtime environment for server-side and networking applications.
JAVASCRIPT PERFORMANCE PATTERN - A PresentationHabileLabs
Let's have an idea about JAVASCRIPT PERFORMANCE PATTERN, what is it? why do we need to use this? Etc.
Check out this presentation for all you need to know about javascript performance patterns.
A Presentation on MongoDB Introduction - HabilelabsHabileLabs
This document introduces MongoDB, an open-source document-oriented database. It discusses how MongoDB stores data as JSON-like documents rather than in tables, supports dynamic schemas, and is horizontally scalable. Some common use cases for MongoDB are also listed, including single view applications, IoT, mobile, real-time analytics, personalization, catalogs, and content management. The document concludes by covering how Habilelabs uses MongoDB with Node.js for REST API projects.
Why MongoDB over other Databases - HabilelabsHabileLabs
MongoDB is the faster-growing database. It is an open-source document and leading NoSQL database with the scalability and flexibility that you want with the querying and indexing that you need. In this Document, I presented why to choose MongoDB is over another database.
Poorly designed API may be cause of security issues and unsafe code.
A robust and strong design is a key factor for API success.
You should know these 4 Basic Rest API Design Guidelines.
https://goo.gl/QaxpSA
Neural representations have shown the potential to accelerate ray casting in a conventional ray-tracing-based rendering pipeline. We introduce a novel approach called Locally-Subdivided Neural Intersection Function (LSNIF) that replaces bottom-level BVHs used as traditional geometric representations with a neural network. Our method introduces a sparse hash grid encoding scheme incorporating geometry voxelization, a scene-agnostic training data collection, and a tailored loss function. It enables the network to output not only visibility but also hit-point information and material indices. LSNIF can be trained offline for a single object, allowing us to use LSNIF as a replacement for its corresponding BVH. With these designs, the network can handle hit-point queries from any arbitrary viewpoint, supporting all types of rays in the rendering pipeline. We demonstrate that LSNIF can render a variety of scenes, including real-world scenes designed for other path tracers, while achieving a memory footprint reduction of up to 106.2x compared to a compressed BVH.
https://arxiv.org/abs/2504.21627
Data Virtualization: Bringing the Power of FME to Any ApplicationSafe Software
Imagine building web applications or dashboards on top of all your systems. With FME’s new Data Virtualization feature, you can deliver the full CRUD (create, read, update, and delete) capabilities on top of all your data that exploit the full power of FME’s all data, any AI capabilities. Data Virtualization enables you to build OpenAPI compliant API endpoints using FME Form’s no-code development platform.
In this webinar, you’ll see how easy it is to turn complex data into real-time, usable REST API based services. We’ll walk through a real example of building a map-based app using FME’s Data Virtualization, and show you how to get started in your own environment – no dev team required.
What you’ll take away:
-How to build live applications and dashboards with federated data
-Ways to control what’s exposed: filter, transform, and secure responses
-How to scale access with caching, asynchronous web call support, with API endpoint level security.
-Where this fits in your stack: from web apps, to AI, to automation
Whether you’re building internal tools, public portals, or powering automation – this webinar is your starting point to real-time data delivery.
Agentic AI Explained: The Next Frontier of Autonomous Intelligence & Generati...Aaryan Kansari
Agentic AI Explained: The Next Frontier of Autonomous Intelligence & Generative AI
Discover Agentic AI, the revolutionary step beyond reactive generative AI. Learn how these autonomous systems can reason, plan, execute, and adapt to achieve human-defined goals, acting as digital co-workers. Explore its promise, key frameworks like LangChain and AutoGen, and the challenges in designing reliable and safe AI agents for future workflows.
Sticky Note Bullets:
Definition: Next stage beyond ChatGPT-like systems, offering true autonomy.
Core Function: Can "reason, plan, execute and adapt" independently.
Distinction: Proactive (sets own actions for goals) vs. Reactive (responds to prompts).
Promise: Acts as "digital co-workers," handling grunt work like research, drafting, bug fixing.
Industry Outlook: Seen as a game-changer; Deloitte predicts 50% of companies using GenAI will have agentic AI pilots by 2027.
Key Frameworks: LangChain, Microsoft's AutoGen, LangGraph, CrewAI.
Development Focus: Learning to think in workflows and goals, not just model outputs.
Challenges: Ensuring reliability, safety; agents can still hallucinate or go astray.
Best Practices: Start small, iterate, add memory, keep humans in the loop for final decisions.
Use Cases: Limited only by imagination (e.g., drafting business plans, complex simulations).
Microsoft Build 2025 takeaways in one presentationDigitalmara
Microsoft Build 2025 introduced significant updates. Everything revolves around AI. DigitalMara analyzed these announcements:
• AI enhancements for Windows 11
By embedding AI capabilities directly into the OS, Microsoft is lowering the barrier for users to benefit from intelligent automation without requiring third-party tools. It's a practical step toward improving user experience, such as streamlining workflows and enhancing productivity. However, attention should be paid to data privacy, user control, and transparency of AI behavior. The implementation policy should be clear and ethical.
• GitHub Copilot coding agent
The introduction of coding agents is a meaningful step in everyday AI assistance. However, it still brings challenges. Some people compare agents with junior developers. They noted that while the agent can handle certain tasks, it often requires supervision and can introduce new issues. This innovation holds both potential and limitations. Balancing automation with human oversight is crucial to ensure quality and reliability.
• Introduction of Natural Language Web
NLWeb is a significant step toward a more natural and intuitive web experience. It can help users access content more easily and reduce reliance on traditional navigation. The open-source foundation provides developers with the flexibility to implement AI-driven interactions without rebuilding their existing platforms. NLWeb is a promising level of web interaction that complements, rather than replaces, well-designed UI.
• Introduction of Model Context Protocol
MCP provides a standardized method for connecting AI models with diverse tools and data sources. This approach simplifies the development of AI-driven applications, enhancing efficiency and scalability. Its open-source nature encourages broader adoption and collaboration within the developer community. Nevertheless, MCP can face challenges in compatibility across vendors and security in context sharing. Clear guidelines are crucial.
• Windows Subsystem for Linux is open-sourced
It's a positive step toward greater transparency and collaboration in the developer ecosystem. The community can now contribute to its evolution, helping identify issues and expand functionality faster. However, open-source software in a core system also introduces concerns around security, code quality management, and long-term maintenance. Microsoft’s continued involvement will be key to ensuring WSL remains stable and secure.
• Azure AI Foundry platform hosts Grok 3 AI models
Adding new models is a valuable expansion of AI development resources available at Azure. This provides developers with more flexibility in choosing language models that suit a range of application sizes and needs. Hosting on Azure makes access and integration easier when using Microsoft infrastructure.
New Ways to Reduce Database Costs with ScyllaDBScyllaDB
How ScyllaDB’s latest capabilities can reduce your infrastructure costs
ScyllaDB has been obsessed with price-performance from day 1. Our core database is architected with low-level engineering optimizations that squeeze every ounce of power from the underlying infrastructure. And we just completed a multi-year effort to introduce a set of new capabilities for additional savings.
Join this webinar to learn about these new capabilities: the underlying challenges we wanted to address, the workloads that will benefit most from each, and how to get started. We’ll cover ways to:
- Avoid overprovisioning with “just-in-time” scaling
- Safely operate at up to ~90% storage utilization
- Cut network costs with new compression strategies and file-based streaming
We’ll also highlight a “hidden gem” capability that lets you safely balance multiple workloads in a single cluster. To conclude, we will share the efficiency-focused capabilities on our short-term and long-term roadmaps.
As data privacy regulations become more pervasive across the globe and organizations increasingly handle and transfer (including across borders) meaningful volumes of personal and confidential information, the need for robust contracts to be in place is more important than ever.
This webinar will provide a deep dive into privacy contracting, covering essential terms and concepts, negotiation strategies, and key practices for managing data privacy risks.
Whether you're in legal, privacy, security, compliance, GRC, procurement, or otherwise, this session will include actionable insights and practical strategies to help you enhance your agreements, reduce risk, and enable your business to move fast while protecting itself.
This webinar will review key aspects and considerations in privacy contracting, including:
- Data processing addenda, cross-border transfer terms including EU Model Clauses/Standard Contractual Clauses, etc.
- Certain legally-required provisions (as well as how to ensure compliance with those provisions)
- Negotiation tactics and common issues
- Recent lessons from recent regulatory actions and disputes
Adtran’s SDG 9000 Series brings high-performance, cloud-managed Wi-Fi 7 to homes, businesses and public spaces. Built on a unified SmartOS platform, the portfolio includes outdoor access points, ceiling-mount APs and a 10G PoE router. Intellifi and Mosaic One simplify deployment, deliver AI-driven insights and unlock powerful new revenue streams for service providers.
Co-Constructing Explanations for AI Systems using ProvenancePaul Groth
Explanation is not a one off - it's a process where people and systems work together to gain understanding. This idea of co-constructing explanations or explanation by exploration is powerful way to frame the problem of explanation. In this talk, I discuss our first experiments with this approach for explaining complex AI systems by using provenance. Importantly, I discuss the difficulty of evaluation and discuss some of our first approaches to evaluating these systems at scale. Finally, I touch on the importance of explanation to the comprehensive evaluation of AI systems.
Cyber Security Legal Framework in Nepal.pptxGhimire B.R.
The presentation is about the review of existing legal framework on Cyber Security in Nepal. The strength and weakness highlights of the major acts and policies so far. Further it highlights the needs of data protection act .
Maxx nft market place new generation nft marketing placeusersalmanrazdelhi
PREFACE OF MAXXNFT
MaxxNFT: Powering the Future of Digital Ownership
MaxxNFT is a cutting-edge Web3 platform designed to revolutionize how
digital assets are owned, traded, and valued. Positioned at the forefront of the
NFT movement, MaxxNFT views NFTs not just as collectibles, but as the next
generation of internet equity—unique, verifiable digital assets that unlock new
possibilities for creators, investors, and everyday users alike.
Through strategic integrations with OKT Chain and OKX Web3, MaxxNFT
enables seamless cross-chain NFT trading, improved liquidity, and enhanced
user accessibility. These collaborations make it easier than ever to participate
in the NFT ecosystem while expanding the platform’s global reach.
With a focus on innovation, user rewards, and inclusive financial growth,
MaxxNFT offers multiple income streams—from referral bonuses to liquidity
incentives—creating a vibrant community-driven economy. Whether you
'
re
minting your first NFT or building a digital asset portfolio, MaxxNFT empowers
you to participate in the future of decentralized value exchange.
https://maxxnft.xyz/
Contributing to WordPress With & Without Code.pptxPatrick Lumumba
Contributing to WordPress: Making an Impact on the Test Team—With or Without Coding Skills
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This talk aims to deconstruct the myth that one has to be a developer to contribute to WordPress. In this session, I will share with the audience how to get involved with the WordPress Team, whether a coder or not.
We’ll explore practical ways to contribute, from testing new features, and patches, to reporting bugs. By the end of this talk, the audience will have the tools and confidence to make a meaningful impact on WordPress—no matter the skill set.
Droidal: AI Agents Revolutionizing HealthcareDroidal LLC
Droidal’s AI Agents are transforming healthcare by bringing intelligence, speed, and efficiency to key areas such as Revenue Cycle Management (RCM), clinical operations, and patient engagement. Built specifically for the needs of U.S. hospitals and clinics, Droidal's solutions are designed to improve outcomes and reduce administrative burden.
Through simple visuals and clear examples, the presentation explains how AI Agents can support medical coding, streamline claims processing, manage denials, ensure compliance, and enhance communication between providers and patients. By integrating seamlessly with existing systems, these agents act as digital coworkers that deliver faster reimbursements, reduce errors, and enable teams to focus more on patient care.
Droidal's AI technology is more than just automation — it's a shift toward intelligent healthcare operations that are scalable, secure, and cost-effective. The presentation also offers insights into future developments in AI-driven healthcare, including how continuous learning and agent autonomy will redefine daily workflows.
Whether you're a healthcare administrator, a tech leader, or a provider looking for smarter solutions, this presentation offers a compelling overview of how Droidal’s AI Agents can help your organization achieve operational excellence and better patient outcomes.
A free demo trial is available for those interested in experiencing Droidal’s AI Agents firsthand. Our team will walk you through a live demo tailored to your specific workflows, helping you understand the immediate value and long-term impact of adopting AI in your healthcare environment.
To request a free trial or learn more:
https://droidal.com/
UiPath Community Zurich: Release Management and Build PipelinesUiPathCommunity
Ensuring robust, reliable, and repeatable delivery processes is more critical than ever - it's a success factor for your automations and for automation programmes as a whole. In this session, we’ll dive into modern best practices for release management and explore how tools like the UiPathCLI can streamline your CI/CD pipelines. Whether you’re just starting with automation or scaling enterprise-grade deployments, our event promises to deliver helpful insights to you. This topic is relevant for both on-premise and cloud users - as well as for automation developers and software testers alike.
📕 Agenda:
- Best Practices for Release Management
- What it is and why it matters
- UiPath Build Pipelines Deep Dive
- Exploring CI/CD workflows, the UiPathCLI and showcasing scenarios for both on-premise and cloud
- Discussion, Q&A
👨🏫 Speakers
Roman Tobler, CEO@ Routinuum
Johans Brink, CTO@ MvR Digital Workforce
We look forward to bringing best practices and showcasing build pipelines to you - and to having interesting discussions on this important topic!
If you have any questions or inputs prior to the event, don't hesitate to reach out to us.
This event streamed live on May 27, 16:00 pm CET.
Check out all our upcoming UiPath Community sessions at:
👉 https://community.uipath.com/events/
Join UiPath Community Zurich chapter:
👉 https://community.uipath.com/zurich/
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Protecting Your Sensitive Data with Microsoft Purview - IRMS 2025Nikki Chapple
Session | Protecting Your Sensitive Data with Microsoft Purview: Practical Information Protection and DLP Strategies
Presenter | Nikki Chapple (MVP| Principal Cloud Architect CloudWay) & Ryan John Murphy (Microsoft)
Event | IRMS Conference 2025
Format | Birmingham UK
Date | 18-20 May 2025
In this closing keynote session from the IRMS Conference 2025, Nikki Chapple and Ryan John Murphy deliver a compelling and practical guide to data protection, compliance, and information governance using Microsoft Purview. As organizations generate over 2 billion pieces of content daily in Microsoft 365, the need for robust data classification, sensitivity labeling, and Data Loss Prevention (DLP) has never been more urgent.
This session addresses the growing challenge of managing unstructured data, with 73% of sensitive content remaining undiscovered and unclassified. Using a mountaineering metaphor, the speakers introduce the “Secure by Default” blueprint—a four-phase maturity model designed to help organizations scale their data security journey with confidence, clarity, and control.
🔐 Key Topics and Microsoft 365 Security Features Covered:
Microsoft Purview Information Protection and DLP
Sensitivity labels, auto-labeling, and adaptive protection
Data discovery, classification, and content labeling
DLP for both labeled and unlabeled content
SharePoint Advanced Management for workspace governance
Microsoft 365 compliance center best practices
Real-world case study: reducing 42 sensitivity labels to 4 parent labels
Empowering users through training, change management, and adoption strategies
🧭 The Secure by Default Path – Microsoft Purview Maturity Model:
Foundational – Apply default sensitivity labels at content creation; train users to manage exceptions; implement DLP for labeled content.
Managed – Focus on crown jewel data; use client-side auto-labeling; apply DLP to unlabeled content; enable adaptive protection.
Optimized – Auto-label historical content; simulate and test policies; use advanced classifiers to identify sensitive data at scale.
Strategic – Conduct operational reviews; identify new labeling scenarios; implement workspace governance using SharePoint Advanced Management.
🎒 Top Takeaways for Information Management Professionals:
Start secure. Stay protected. Expand with purpose.
Simplify your sensitivity label taxonomy for better adoption.
Train your users—they are your first line of defense.
Don’t wait for perfection—start small and iterate fast.
Align your data protection strategy with business goals and regulatory requirements.
💡 Who Should Watch This Presentation?
This session is ideal for compliance officers, IT administrators, records managers, data protection officers (DPOs), security architects, and Microsoft 365 governance leads. Whether you're in the public sector, financial services, healthcare, or education.
🔗 Read the blog: https://nikkichapple.com/irms-conference-2025/
Protecting Your Sensitive Data with Microsoft Purview - IRMS 2025Nikki Chapple
Basics of MongoDB
1. Aishwarya Kumar Singh
Software Engineer
Habilelabs.io
Basics of MongoDB
in Windows
Environment
http://www.habilelabs.io
2. CONTENTS
What is MongoDB?
What is NoSQL?
How is NoSQL(MongoDB) different
from conventional RDBMS?
Why MongoDB is important?
Key features of MongoDB
How to install & run MongoDB?
What we get in installation package?
What is JSON
JSON Example
Basic SQL to MongoDB Terminology
Comparison
Major Datatypes in MongoDB
What is ObjectID (_id)?
Basic CRUD operations in MongoDB
Important Query methods in MongoDB
Important operators
RDBMS Where clause equivalents in
MongoDB
Where MongoDB is best suited?
Excellent MongoDB learning references
3. WHAT IS MONGODB?
• MongoDB name comes from HuMONGOus data.
• According to the official website of MongoDB it is defined in the
following way –
MongoDB is a document database with the scalability and
flexibility that you want with the querying and indexing that
you need.
• It is a NoSQL Database.
• It is Open source and free to use.
• It is a cross-platform database which works with almost every platform
(Windows, mac, Linux) .
• It stores data in flexible, JSON like documents.
4. WHAT IS NOSQL?
• The mechanism of storing and retrieving the data without using the conventional way of
storage i.e., inside table.
• The storage mechanism adapted here is the non relational form of data.
• NoSQL databases are also sometimes referred as “Not Only SQL”
• Structured Query Language (SQL) adapts the conventional methods of having relations
and some proper schema but NoSQL is completely different and it follows no schema.
• NoSQL databases are divided in the following parts:
• Document databases: used to store semi-structured data as documents (MongoDB,
ArangoDB, RethinkDB, CouchDB). Data is represented as a JSON document.
• Graph stores: used to store the information about the network of the data (Neo4J,
GraphBase, WhiteDB)
• Key-value stores: Data is stored in the form of key-value pairs. They are the simplest NoSQL
Databases (Redis, DynamoDB, Riak, Berkeley DB).
• Wide-column stores: It uses tables, rows and columns but the names and formats of the
columns can vary from row to row in the same table (Cassandra and HBase).
5. HOW NOSQL IS DIFFERENT FROM CONVENTIONAL RDBMS?
• SQL databases are table based databases whereas NoSQL databases are document based,
key-value pairs, graph databases or wide-column stores.
• SQL databases have predefined schema whereas NoSQL databases have dynamic schema for
unstructured data.
• SQL databases are vertically scalable whereas the NoSQL databases are horizontally scalable.
• SQL databases are not best suited for hierarchal data storage whereas NoSQL is best suited
for it.
RDBMS (SQL) NoSQL
Base Table (rows and columns) Document, key-value pairs, graph and
wide-column stores
Schema Predefined Dynamic
Scalability Vertical Horizontal
Category Relational Non-relational or Distributed
Big Data Preference Preferred Not preferred
Complex Query Preference Preferred Not preferred
Hierarchical Data Storage Preference Not preferred Preferred
6. WHY MONGODB IS IMPORTANT ?
• MongoDB is important in many aspects and some of those major points are as
follows:
1. It is document oriented and does not need the row and column format of the data.
2. It gives high performance.
3. It is dynamic in nature where you don’t need to predefine a schema like in
conventional RDBMS.
4. There is no concept of Joins in MongoDB instead it has $lookup aggregation
operator in versions >=3.2. There is a mongoose alternative as well which is called as
populate() that is used to reference documents in other collections.
5. MongoDB stores data in JSON format which allows to send the data in whatever form
you want.
7. KEY FEATURES OF MONGODB ?
1. Data is stored in BSON and presented in JSON.
2. Server-side JavaScript is supported (JavaScript expressions and functions).
3. Document oriented database where there are no tables and no row-based
data.
4. NoSQL, where there is no schema. Documents can have different structures.
Documents can be embedded. This is specifically designed for horizontal
scaling.
5. By default, there is a primary key (_id), which is an auto-generated field for
every document.
6. Sharding is supported which is very much essential for horizontal scaling and
replication.
7. It has automatic load balancing configurations.
8. Fault Tolerance is natively built in MongoDB.
9. HOW TO INSTALL & RUN MONGODB ?
• To install the MongoDB you need to visit the download section of the official
website. Visit the following link: https://www.mongodb.com/download-
center/community.
Select the version, OS and the package there and then click download.
• After download is completed double click the file (e.g.:- mongodb-win32-x86_64-
2008plus-ssl-3.4.5-signed.msi). This will start the installation.
• Go through all the steps. Simply click next on each step and at the last step click on
Finish button. This will install the MongoDB on your system.
RUNNING THE MONGODB IN SYSTEM:
• Create the folder C:datadb (In this case after creating the folder, you need to
double click the mongod.exe file or just need to start the command line terminal and
run the command mongod).
To be continued…
10. HOW TO INSTALL & RUN MONGODB ?
…in continuation
• Alternatively you can create the folder at a different location and give its
reference in mongo.config file. Then in mongo.bat file write the reference of
the mongo.config file and run it whenever you want to start the mongodb
server.
• Mongo.config file has some other parameters which are described in the
below image.
• It comprises database path reference, log file path reference and port
number reference.
To be continued…
11. HOW TO INSTALL & RUN MONGODB ?
…in continuation
• The mongo.bat file will have a reference to mongo.config file.
• The command written inside the mongo.bat file is:
mongod -f mongo.config
• It is shown in the below image.
• This will allow the server to read the config file and refer the location of the
database.
• The default port that the mongodb server reads is 27017.
12. WHAT IS THERE IN INSTALLATION PACKAGE ?
• MongoDB comes with handy tools which are bundled together at a single place.
Those tools are as follows:
1. mongod: Mongo demon which is the server.
2. mongo: It is a CLI based client.
3. mongos: It is a mongodb sharing routing service(Used for sharding).
4. mongostat: It is used for monitoring the Quick Overview of the running instance.
5. mongotop: It is used for monitoring the Read and Write of an instance.
NOTE:
1. To start the server we just need the mongod file.
2. For the ease of learning and exploring MongoDB, you can install any MongoDB GUI
tool at this point (Robo 3T, QueryAssist, NoSQLBooster, Studio 3T, MongoDB Compass,
Mongo Management Studio, NoSQL Manager, NoSQL Client, Navicat for MongoDB)
…to be continued
13. WHAT IS THERE IN INSTALLATION PACKAGE ?
…in continuation
mongorestore: It loads data from the Binary DB dump.
bsondump & mongodump: It creates binary dump.
mongooplog: It is used for the purpose of the replication from the oplog.
mongoexport & mongoimport: It is used to export or import files(generally JSON
& CSV).
mongoperf: It is used to check the Disk IO.
mongofiles: It is basically used for GridFS functionality.
14. WHAT IS JSON?
• Before proceeding any further you must know what is JSON as MongoDB data
is always represented in the JSON format. So, here are some of the essential
points related to JSON.
1. JSON stands for JavaScript Object Notation. It is a collection of key-value
pairs. Keys must be written inside single or double quotes. Values can have any
data type (Array, string, Boolean etc.)
2. JSON file must start and end with a curly brace.
3. Collection of key-value pair Various languages recognize it as an object,
record, struct, dictionary, hash table, keyed list, or associative array.
4. Object is surrounded by the curly braces and key-value pairs are separated by
comma.
5. Array is surrounded by square braces and each value is separated with a
comma.
6. Value can be of any type string, number, object, array, true, false, null
15. JSON EXAMPLE
{
“firstName”: “John”,
“lastName”: “Doe”,
“age”: 25,
“address”: {
“streetAddress”: “221B Bakers Street”,
“city”: “London”,
“state”: “ENG”,
“postalCode”: “200001”
},
}
Notice here the key-value pair form of data that is embedded inside the curly braces.
16. BASIC SQL TO MONGODB TERMINOLOGY COMPARISON
SQL MongoDB
database database
table collection
row document or BSON document
column field
index index
table joins $lookup, embedded documents
primary key (need to specify column or combination of
column)
primary key (automatically set to _id field)
aggregation aggregation pipeline
MongoDB MySQL Oracle Informix DB2
Database Server mongod mysqld oracle IDS DB2 Server
Database Client mongo mysql sqlplus DB-Access DB2 Client
Database Executables Comparison:
Terminology & Concept Comparison:
17. MAJOR DATATYPES IN MONGODB ?
1. String
2. Integer
3. Boolean
4. Double
5. Min/Max keys
6. Arrays
7. Timestamp
8. Object
9. Null
10. Symbol
11. Date
12. ObjectID
13. Binary data
14. Code
15. Regular expression
18. • ObjectId in the MongoDB is same as the primary key in the conventional
RDBMS.
• It is by default set by MongoDB for every document that is created inside any
collection.
• ObjectIds are small, unique, fast to generate and ordered.
• ObjectId values comprises of a 12 bytes hexadecimal number which is unique
for every document.
• _id: ObjectId(4 bytes timestamp, 3 bytes machine id, 2 bytes process id,
• 3 bytes counter)
• "_id": ObjectId("5901832c91427cac52e9ea8f")
WHAT IS objectId (_id) ?
19. BASIC CRUD OPERATIONS
• The basic operations in every database comprises of the following four
operations:
CREATE
READ
UPDATE
DELETE
• In MongoDB these four basic operations are achieved using the unique style
of writing. But before actually starting with the data, you must first create a
database.
• In MongoDB, database is created using the use command.
…to be continued
20. BASIC CRUD OPERATIONS
STARTING THE MONGODB INSTANCE IN THE TERMINAL
1. Go to the terminal and give the command mongo there so as to start the MongoDB
CLI.
• This will start the mongo instance in the terminal from where you can work on mongodb
and fire queries.
…to be continued
21. BASIC CRUD OPERATIONS
…in continuation
CREATING THE DATABASE USING THE use COMMAND
• Go to the terminal and write the command use <database_name> where
database name will be replaced by the name of your database. This will create
the database with the name which you want.
• Alternatively it can be achieved by using any of the GUI tool and from there you
can create the new database. But this GUI tool will first need to be connected to
the host at the desired port number.
…to be continued
22. BASIC CRUD OPERATIONS
The GUI tool which is shown above is QueryAssist
You can Give a name to the instance from the tool.
…to be continued
23. BASIC CRUD OPERATIONS
By this way you can create the database in MongoDB.
Observe the note written in the Create Database Pop Up
…to be continued
24. BASIC CRUD OPERATIONS
NOTE: You can ensure that your database has
been created or not by using the show
databases or show dbs command. The
database will only appear when you have at
least one collection inside it.
To create a collection inside the recently
created database, you must use the insert
command:
db.employee.insert({'name': 'John Doe',
'empId': 'HL0014’});
Now when you hit the show dbs or show
databases command, it will show your
database.
…to be continued
25. BASIC CRUD OPERATIONS
DROPPING A DATABASE
To drop a database in MongoDB you need
to type the following command.
db.dropDatabase()
This will drop the selected database. If database
is not selected then it will delete the default
‘test’ database.
Now you can check through show dbs or show
databases command, that your created
database is dropped.
You can clearly see in the picture that the
habileMongo database is now not listed. It
was dropped using the command above.
…to be continued
26. BASIC CRUD OPERATIONS
For previous operation’s result to be visible, one must first create a
collection inside it. So, let’s start with CRUD operations.
CREATE
For creating a collection use the following command
db.createCollection(name, options)
…to be continued
Parameter Type Description
Name String It is the name of the collection that is to be created
Options Document Specifies option about the memory size and indexing.
This is completely optional.
27. BASIC CRUD OPERATIONS
Options can have the following fields:
…to be continued
Field Type Description
capped Boolean
(Optional) If true, enables a capped collection. Capped collection is a fixed
size collection that automatically overwrites its oldest entries when it
reaches its maximum size. If you specify true, you need to specify size
parameter also.
autoIndexId Boolean
(Optional) If true, automatically create index on _id fields. Default value is
false.
size number
(Optional) Specifies a maximum size in bytes for a capped collection. If
capped is true, then you need to specify this field also.
max number
(Optional) Specifies the maximum number of documents allowed in the
capped collection.
28. BASIC CRUD OPERATIONS
EXAMPLE:
1. Without Options parameter –
db.createCollection(‘Employees’);
This will create the Employees collection.
2. With Options parameter
db.createCollection(‘Employees’, {capped: true, autoIndexId: true, size: 6142800, max:
10000});
…to be continued
29. BASIC CRUD OPERATIONS
INSERT DOCUMENT
For inserting the document in MongoDB collection, you need to write
the following command:
db.collection_name.insert(document)
Where in place of collection name you can place your collection name.
db.Employees.insert({‘name’: ‘John Doe’, ‘empId’: ‘HL0014’})
…to be continued
30. BASIC CRUD OPERATIONS
INSERT DOCUMENT
To insert multiple documents inside a single query, you must pass an
array of documents in the insert() command:
db.Employees.insert([{'name': 'John Smith', 'empId':
'HL0015'},{'name': 'Dwane Simmons', 'empId': 'HL0016'}]);
…to be continued
31. BASIC CRUD OPERATIONS
UPDATE
For updating any document, an update() or save() method is used:
db.Employees.update({'name': 'John Smith’},{$set:{'name': 'John
Smith Carlos’}});
NOTE: By default mongodb will update only a single document. To
update multiple documents , there is a need to set the ‘multi’
parameter to true.
db.Employees.update({'name': 'John Smith’},{$set:{'name': 'John Smith
Carlos’}}, {multi: true});
…to be continued
32. BASIC CRUD OPERATIONS
UPDATE
Using save() method:
Save method will replace the existing document with the new document passed in the
save() method.
db.Employees.save({"_id" : ObjectId("5bef7ca23a929140015e491f"),'name':
'John Smith Carlos', 'empId':'HL0017’});
NOTE: If Save method is used without _id, then it will update the document else
it will insert a document.
…to be continued
33. BASIC CRUD OPERATIONS
DELETE
To delete a document , MongoDB has remove() method.
db.Employees.remove({'name': 'John Smith Carlos’});
This will remove all the documents matching with the conditions.
To remove only one matching document there is deleteOne() method or
remove() method with justOne parameter.
…to be continued
34. BASIC CRUD OPERATIONS
DELETE
To delete a document , MongoDB has remove() method.
db.Employees.deleteOne({'name': 'John Smith Carlos’});
The other way to delete single document is : use the findOne() method first
to find the matching first document and then use remove() method.
…to be continued
35. BASIC CRUD OPERATIONS
DELETE
This way you can remove a particular document from the collection.
findOne() method searches all the data and returns the first matching
document. You can pass the condition inside the findOne() method.m
NOTE: If you don’t specify the deletion criteria (db.Employees.remove()),
then it will delete all the documents inside the collection.
36. IMPORTANT PROJECTION & QUERY METHODS
find()
find() is the essential projection method which helps in selecting only the
necessary data.
db.Employees.find({});
findOne()
This method returns the first matched document from the collection.
You need to specify the condition inside the findOne() method.
db.Employees.findOne({'name': 'John Smith Carlos’});
pretty()
This method is used to display the text in the formatted way.
…to be continued
37. IMPORTANT PROJECTION & QUERY METHODS
distinct()
distinct() is the essential method which helps in returning an array of documents that
have distinct values for a specified field.
db.Employees.distinct({‘name’});
isCapped()
This method is used to check whether that collection is capped or not.
db.Employees.isCapped();
It will return a Boolean value. If capped then true other wise false.
limit()
This method is used to limit the records in MongoDB. It accepts the number type
argument.
db.Employees.find({}).limit(2);
38. IMPORTANT PROJECTION & QUERY
METHODS
skip()
This method is used to skip the number of documents. It accepts the
number type argument.
db.Employees.find({}).limit(1).skip(1);
sort()
This method is used to sort the documents in MongoDB.
db.Employees.find({}).sort({‘name’: -1});
This will sort the document in descending order on the field name.
…to be continued
39. IMPORTANT OPERATORS
AND
This is the operator used to query the data with AND relation. It will
search the document satisfying the conditions that you pass in the
query.
db.Employees.find({$and: [{‘name’: ‘John Smith Carlos’},
{‘EmpId’: ‘HL0020’}]});
OR
This operator is used to query the data with OR relation. It will search
the document and return the result if any of the specified condition is
fulfilled.
db.Employees.find({$or: [{‘name’: ‘John Smith Carlos’}, {‘EmpId’:
‘HL0020’}]});
40. RDBMS WHERE CLAUSE EQUIVALENTS IN
MONGODB
Operation Syntax Example RDBMS Equivalent
Equality {<key>:<value>} db.Employees.find({"name":"John
Doe"}).pretty()
where name = John Doe'
Less Than {<key>:{$lt:<value>}} db.Employees.find({"salary":{$lt:20000}}).
pretty()
where salary < 20000
Less Than Equals {<key>:{$lte:<value>}} db.Employees.find({"salary":{$lte:20000}}
).pretty()
where salary <= 20000
Greater Than {<key>:{$gt:<value>}} db.Employees.find({"salary":{$gt:20000}})
.pretty()
where salary > 20000
Greater Than
Equals
{<key>:{$gte:<value>}} db.Employees.find({"salary":{$gte:20000}}
).pretty()
where likes >= 20000
Not Equals {<key>:{$ne:<value>}} db.Employees.find({"salary":{$ne:20000}})
.pretty()
where likes != 20000
41. WHERE MONGODB IS BEST SUITABLE?
MongoDB is best suited for unstructured and semi-structured data such
as:
• Social media posts
• Web pages
• Emails
• Medical records
• Reports
• Raw data from marketing researches
• Scientific data
42. EXCELLENT MONGODB LEARNING
REFERENCES
• SQL to MongoDB mapping Chart
https://docs.mongodb.com/manual/reference/sql-comparison/
• What is NoSQL?
https://www.mongodb.com/nosql-explained
• MongoDB and MySQL Comparison
https://www.mongodb.com/compare/mongodb-mysql
• MongoDB Cheat Sheet
https://blog.codecentric.de/files/2012/12/MongoDB-CheatSheet-
v1_0.pdf
• Organized Reference card – PDF file – Dzone
https://dzone.com/refcardz/mongodb?chapter=1
…to be continued