Best Query Engines

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL. Most results are delivered within seconds. With Athena, there’s no need for complex ETL jobs to prepare your data for analysis. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets. Athena is out-of-the-box integrated with AWS Glue Data Catalog, allowing you to create a unified metadata repository across various services, crawl data sources to discover schemas and populate your Catalog with new and modified table and partition definitions, and maintain schema versioning.

R2 SQL is Cloudflare’s serverless, distributed analytics query engine (currently in open beta) that enables you to run SQL queries over Apache Iceberg tables stored in R2 Data Catalog without needing to manage your own compute clusters. It is built to efficiently query large volumes of data by leveraging metadata pruning, partition-level statistics, file and row-group filtering, and Cloudflare’s globally distributed compute infrastructure to parallelize execution. The system works by integrating with R2 object storage and an Iceberg catalog layer, so you can ingest data via Cloudflare Pipelines into Iceberg tables, and then query that data with minimal overhead. Queries can be issued via the Wrangler CLI or HTTP API (with an API token granting permissions across R2 SQL, Data Catalog, and storage). During the open beta period, using R2 SQL itself is not billed, only storage and standard R2 operations incur charges.

Parallel query engine with time- and symbol-indexed data access. Extended SQL syntax with advanced filtering and aggregations. Consolidate quotes, trades, snapshots, and reference data in one place. Strategy backtesting on high-frequency data. Quantitative and market microstructure research. Granular transaction cost analysis and rollup reporting. Market surveillance and anomaly detection. Non-transparent ETF/ETN decomposition. FAST, SBE, and proprietary protocols. Plain text protocol. Consolidated and direct feeds. Built-in latency monitoring tools. End-of-day archives. ETL from institutional and retail financial data platforms. Parallel SQL engine with syntax extensions. Advanced filtering by trading session, auction stage, index composition. Optimized aggregates for OHLCV and VWAP calculations. Interactive SQL console with auto-completion. API endpoint for programmatic integration. Scheduled SQL reporting with email, file, and web delivery. JDBC and ODBC drivers.

Don’t let app, device, or game crashes get in the way of a great experience. Backtrace takes all the manual labor out of cross-platform crash and exception management so you can focus on shipping. Cross-platform callstack and event aggregation and monitoring. Process errors from panics, core dumps, minidumps, and during runtime across your stack with a single system. Backtrace generates structured, searchable error reports from your data. Automated analysis cuts down on time to resolution by surfacing important signals that lead engineers to crash root cause. Never worry about missing a clue with rich integrations into dashboards, notification, and workflow systems. Answer the questions that matter to you with Backtrace’s rich query engine. View a high-level overview of error frequency, prioritization, and trends across all your projects. Search through key data points and your own custom data across all your errors.

A hybrid SQL-on-Hadoop engine delivering advanced, security-rich data query across enterprise big data sources, including Hadoop, object storage and data warehouses. IBM Db2 Big SQL is an enterprise-grade, hybrid ANSI-compliant SQL-on-Hadoop engine, delivering massively parallel processing (MPP) and advanced data query. Db2 Big SQL offers a single database connection or query for disparate sources such as Hadoop HDFS and WebHDFS, RDMS, NoSQL databases, and object stores. Benefit from low latency, high performance, data security, SQL compatibility, and federation capabilities to do ad hoc and complex queries. Db2 Big SQL is now available in 2 variations. It can be integrated with Cloudera Data Platform, or accessed as a cloud-native service on the IBM Cloud Pak® for Data platform. Access and analyze data and perform queries on batch and real-time data across sources, like Hadoop, object stores and data warehouses.

SPListX for SharePoint is a powerful rule-based query engine application to export document / picture library contents and associated metadata and list items, including associated file attachments to Windows File System. Export SharePoint site, libraries, folders, documents, list items, version histories, metadata and permissions to the desired destination location in Windows File System. SPListX supports SharePoint 2019 / SharePoint 2016 / SharePoint 2013 / SharePoint 2010 / SharePoint 2007 / SharePoint 2003 & Office 365.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.

Perhaps you want to give your clients access to their LIMS data and reports via the web. AIS labPortal allows you to do just that. Paper copies of sample analyses needn’t be sent out in the post to customers. Using their unique login and security password, clients can access data from their computer, which is not only safer and less time-consuming but also more environmentally friendly. labPortal is a web-based portal that securely stores your clients’ sample information and data in the cloud, allowing them to easily access it instantly from their own desktop, tablet or phone. The labPortal interface is 'inbox' style which is simple and easy to use with an enhanced query engine, conditional highlighting and Microsoft Excel export. The software features a simple and easy-to-use sample registration form which allows users to pre-register samples online. Transcribing data is a time-consuming and tedious activity.

Qubole is a simple, open, and secure Data Lake Platform for machine learning, streaming, and ad-hoc analytics. Our platform provides end-to-end services that reduce the time and effort required to run Data pipelines, Streaming Analytics, and Machine Learning workloads on any cloud. No other platform offers the openness and data workload flexibility of Qubole while lowering cloud data lake costs by over 50 percent. Qubole delivers faster access to petabytes of secure, reliable and trusted datasets of structured and unstructured data for Analytics and Machine Learning. Users conduct ETL, analytics, and AI/ML workloads efficiently in end-to-end fashion across best-of-breed open source engines, multiple formats, libraries, and languages adapted to data volume, variety, SLAs and organizational policies.

Quasar's brain is QuasarDB, a high-performance, distributed, column-oriented timeseries database management system designed from the ground up to deliver real-time on petascale use cases. Up to 20X less disk usage. Quasardb ingestion and compression capabilities are unmatched. Up to 10,000X faster feature extraction. QuasarDB can extract features in real-time from the raw data, thanks to the combination of a built-in map/reduce query engine, an aggregation engine that leverages SIMD from modern CPUs, and stochastic indexes that use virtually no disk space. The most cost-effective timeseries solution, thanks to its ultra-efficient resource usage, the capability to leverage object storage (S3), unique compression technology, and fair pricing model. Quasar runs everywhere, from 32-bit ARM devices to high-end Intel servers, from Edge Computing to the cloud or on-premises.

Amazon Timestream is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day up to 1,000 times faster and at as little as 1/10th the cost of relational databases. Amazon Timestream saves you time and cost in managing the lifecycle of time series data by keeping recent data in memory and moving historical data to a cost optimized storage tier based upon user defined policies. Amazon Timestream’s purpose-built query engine lets you access and analyze recent and historical data together, without needing to specify explicitly in the query whether the data resides in the in-memory or cost-optimized tier. Amazon Timestream has built-in time series analytics functions, helping you identify trends and patterns in your data in near real-time.