Best Embedded Database Apps for iPad of 2025

Compare the Top Embedded Database Apps for iPad as of July 2025

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What are Embedded Database Apps for iPad?

Embedded database systems are lightweight, self-contained databases that are integrated directly into applications, allowing data management without requiring a separate database server. They are optimized for performance and simplicity, often running within the same process as the host application, making them ideal for use in mobile apps, IoT devices, and small-scale applications. These databases support SQL or other query languages and offer full database functionality, including transaction management and data integrity. Embedded database systems are designed to operate with minimal configuration, providing fast, reliable data storage and retrieval within constrained environments. Their ease of integration and low resource usage make them essential for applications that need efficient local data management without the overhead of external databases. Compare and read user reviews of the best Embedded Database apps for iPad currently available using the table below. This list is updated regularly.

1

RaimaDB

Raima

RaimaDB is an embedded time series database for IoT and Edge devices that can run in-memory. It is an extremely powerful, lightweight and secure RDBMS. Field tested by over 20 000 developers worldwide and has more than 25 000 000 deployments. RaimaDB is a high-performance, cross-platform embedded database designed for mission-critical applications, particularly in the Internet of Things (IoT) and edge computing markets. It offers a small footprint, making it suitable for resource-constrained environments, and supports both in-memory and persistent storage configurations. RaimaDB provides developers with multiple data modeling options, including traditional relational models and direct relationships through network model sets. It ensures data integrity with ACID-compliant transactions and supports various indexing methods such as B+Tree, Hash Table, R-Tree, and AVL-Tree.

5 Ratings

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2

eXtremeDB

McObject

How is platform independent eXtremeDB different? - Hybrid data storage. Unlike other IMDS, eXtremeDB can be all-in-memory, all-persistent, or have a mix of in-memory tables and persistent tables - Active Replication Fabric™ is unique to eXtremeDB, offering bidirectional replication, multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud), compression to maximize limited bandwidth networks and more - Row & Columnar Flexibility for Time Series Data supports database designs that combine row-based and column-based layouts, in order to best leverage the CPU cache speed - Embedded and Client/Server. Fast, flexible eXtremeDB is data management wherever you need it, and can be deployed as an embedded database system, and/or as a client/server database system -A hard real-time deterministic option in eXtremeDB/rt Designed for use in resource-constrained, mission-critical embedded systems. Found in everything from routers to satellites to trains to stock markets worldwide

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3

VelocityDB

VelocityDB

VelocityDB is a database engine like no other. It can store data faster and more efficiently than any other solution at a fraction of the cost of other database engines. It stores .NET objects as they are with no mapping to tables, JSON or XML. VelocityGraph is an add on open source property graph database that can be used in conjunction with the VelocityDB object database. Object and graph database engine VelocityDB is a C# .NET noSQL object fatabase, extended as graph database is VelocityGraph. World’s fastest most scalable & flexible database. A bug reported with a reproducible test case is usually fixed within a week. The most important benefit is the flexibility that this database system provides. No other types of database system lets you fine tune your application to the finest details. Using VelocityDB, you can choose the best possible data structures for your application. You can control where you place the data persistently and how it's indexed and accessed.

Starting Price: $200 per 6 moths

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4

Actian Zen

Actian

Actian Zen is an embedded, high-performance, and low-maintenance database management system designed for edge applications, mobile devices, and IoT environments. It offers a seamless integration of SQL and NoSQL data models, providing flexibility for developers working with structured and unstructured data. Actian Zen is known for its small footprint, scalability, and high reliability, making it ideal for resource-constrained environments where consistent performance and minimal administrative overhead are essential. With built-in security features and a self-tuning architecture, it supports real-time data processing and analytics without the need for constant monitoring or maintenance. Actian Zen is widely used in industries like healthcare, retail, and manufacturing, where edge computing and distributed data environments are critical for business operations.

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5

Ditto

Ditto

Ditto is the only mobile database with built-in edge device connectivity and resiliency, enabling apps to synchronize without relying on a central server or constant cloud connectivity. Through the use of CRDTs and P2P mesh replication, Ditto's technology enables you to build collaborative, resilient applications where data is always available and up-to-date for every user, and can even be synced in completely offline situations. This allows you to keep mission-critical systems online when it matters most. Devices running Ditto apps can discover and communicate with each other directly, forming an ad-hoc mesh network rather than routing everything through a cloud server. The platform automatically handles the complexity of discovery and connectivity using both online and offline channels – Bluetooth, peer-to-peer Wi-Fi, local LAN, WiFi, Cellular – to find nearby devices and sync data changes in real-time.

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6

LevelDB

Google

LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values. Keys and values are arbitrary byte arrays. Data is stored sorted by key. Callers can provide a custom comparison function to override the sort order. Multiple changes can be made in one atomic batch. Users can create a transient snapshot to get a consistent view of data. Forward and backward iteration is supported over the data. Data is automatically compressed using the Snappy compression library. External activity (file system operations etc.) is relayed through a virtual interface so users can customize the operating system interactions. We use a database with a million entries. Each entry has a 16 byte key, and a 100 byte value. Values used by the benchmark compress to about half their original size. We list the performance of reading sequentially in both the forward and reverse direction, and also the performance of a random lookup.

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