List of the Top 17 Free Embedded Database Systems in 2025

SQLite is a library written in C that delivers a compact, efficient, and fully-featured SQL database engine that is both reliable and widely used. It is regarded as the most popular database engine in the world, integrated into virtually every mobile device and most computers, along with countless applications that people utilize on a daily basis. Functioning as an in-process library, SQLite serves as a self-contained, serverless, and zero-configuration transactional SQL database engine. The source code is in the public domain, allowing anyone to utilize it freely for both commercial and personal endeavors. Thanks to its extensive integration and deployment across various platforms, SQLite has become an essential resource for developers engaged in significant projects. Its remarkable adaptability and user-friendliness are key factors that contribute to its unparalleled popularity within the database arena, making it a go-to choice for many. This widespread adoption showcases its importance in modern software development and data management practices.

MySQL is recognized as the leading open source database in the world. Its impressive history of reliability, performance, and ease of use has made it the go-to choice for many web applications, including major platforms like Facebook, Twitter, and YouTube, as well as the five most visited websites. Additionally, MySQL is a popular option for embedded database solutions, with many independent software vendors and original equipment manufacturers distributing it. The database's flexibility and powerful capabilities further enhance its popularity across diverse sectors, making it a critical tool for developers and businesses alike. Its continued evolution ensures that it remains relevant in an ever-changing technological landscape.

Chroma is an open-source embedding database tailored for applications in artificial intelligence. It comes equipped with an extensive array of tools that simplify the process for developers looking to incorporate embedding technology into their projects. The primary goal of Chroma is to create a database that is capable of continuous learning and improvement over time. Users are encouraged to take part in the development process by reporting issues, submitting pull requests, or participating in our Discord community where they can offer feature suggestions and connect with fellow users. Your contributions are essential as we aim to refine Chroma's features and overall user experience, ensuring it meets the evolving needs of the AI community. Engaging with Chroma not only helps shape its future but also fosters a collaborative environment for innovation.

LanceDB is a user-friendly, open-source database tailored specifically for artificial intelligence development. It boasts features like hyperscalable vector search and advanced retrieval capabilities designed for Retrieval-Augmented Generation (RAG), as well as the ability to handle streaming training data and perform interactive analyses on large AI datasets, positioning it as a robust foundation for AI applications. The installation process is remarkably quick, allowing for seamless integration with existing data and AI workflows. Functioning as an embedded database—similar to SQLite or DuckDB—LanceDB facilitates native object storage integration, enabling deployment in diverse environments and efficient scaling down when not in use. Whether used for rapid prototyping or extensive production needs, LanceDB delivers outstanding speed for search, analytics, and training with multimodal AI data. Moreover, several leading AI companies have efficiently indexed a vast array of vectors and large quantities of text, images, and videos at a cost significantly lower than that of other vector databases. In addition to basic embedding capabilities, LanceDB offers advanced features for filtering, selection, and streaming training data directly from object storage, maximizing GPU performance for superior results. This adaptability not only enhances its utility but also positions LanceDB as a formidable asset in the fast-changing domain of artificial intelligence, catering to the needs of various developers and researchers alike.

Perst is a versatile, open-source object-oriented embedded database management system (ODBMS) developed by McObject, available under dual licensing. It offers two distinct versions: one specifically crafted for Java environments and another geared towards C# applications in the Microsoft .NET Framework. This robust database system empowers developers to effectively store, organize, and access objects, achieving remarkable speed while ensuring low memory and storage requirements. Leveraging the object-oriented capabilities of both Java and C#, Perst demonstrates superior performance in benchmarks such as TestIndex and PolePosition compared to other embedded databases in the Java and .NET ecosystems. A notable feature of Perst is its capacity to directly store data in Java and .NET objects, eliminating the need for translation that is common in relational and object-relational databases, which in turn boosts run-time performance. With a streamlined core that consists of just five thousand lines of code, Perst requires minimal system resources, rendering it an appealing choice for environments with limited resources. This efficiency not only enhances developer experience but also significantly improves the responsiveness of applications that incorporate the database, making it a compelling option for a variety of projects. Additionally, its flexibility and performance make it suitable for both small-scale applications and larger, more complex systems.

Firebird is a versatile relational database that adheres to many ANSI SQL standards and offers compatibility across Linux, Windows, and various Unix platforms. Its features include exceptional concurrency, high performance, and strong support for stored procedures and triggers, which contribute to its widespread use in different applications. Since its launch in 1981, Firebird has been employed in various production settings under several different names. The Firebird Project functions autonomously, comprising a team of C and C++ developers, technical advisors, and community supporters who all play a role in the continued enhancement of this multi-platform relational database management system, derived from the source code released by Inprise Corp (now known as Borland Software Corp) on July 25, 2000. In addition, the Firebird Project offers an extensive array of documentation for users, developers, and administrators, including beginner-friendly Quick Start guides and detailed expert articles that delve into various features of the Firebird system. This comprehensive resource guarantees that anyone engaging with Firebird has access to the necessary information to refine their experience and maximize the database's capabilities. As a result, the Firebird community continues to grow, enhancing collaboration and knowledge sharing among its users.

InterSystems Cache® is a robust database solution that supports transaction processing applications worldwide. Its versatility enables it to be utilized in a diverse range of applications, from navigating the vastness of the Milky Way by mapping stars to executing an astounding trillion equity trades daily and overseeing intelligent energy grids. Cache is crafted by InterSystems as a multi-model database management system (DBMS) and application server, accommodating various data models including object-relational and key-value formats. Offering a plethora of APIs, InterSystems Cache allows concurrent data manipulation across several formats, such as key/value, relational/object, document, multidimensional, and more. Users can manage data seamlessly using a wide array of programming languages, including SQL, Java, Node.js, .NET, C++, and Python. Additionally, Cache features an integrated application server that enables the hosting of web applications, supporting various access protocols like CSP, REST, and SOAP, ensuring efficient interaction with Cache data. This multifaceted approach allows developers to create innovative solutions that can scale with their needs.

Berkeley DB consists of a collection of embedded key-value database libraries designed to provide scalable and high-performance data management capabilities for a wide array of applications. The libraries feature simple function-call APIs that facilitate efficient data access and management. By leveraging Berkeley DB, developers can craft customized data management solutions that avoid the usual difficulties associated with bespoke projects. The library includes a variety of dependable building-block technologies that can be tailored to satisfy different application needs, whether for mobile devices or large-scale data centers, addressing both local storage requirements and global distribution challenges. This adaptability allows it to manage data volumes that span from kilobytes to petabytes. Consequently, Berkeley DB stands out as a favored option among developers seeking to implement effective data solutions, making it a versatile tool in the realm of data management. Its capability to cater to diverse environments further solidifies its reputation in the industry.

IBM Informix® stands out as a versatile and effective database solution, seamlessly integrating SQL, NoSQL/JSON, time series, and spatial data. Its user-friendly interface and adaptability make it an ideal option for a variety of environments, encompassing large enterprise data warehouses and smaller application development initiatives. The database's compact design and self-managing capabilities make it especially beneficial for applications involving embedded data management. As the need for IoT data processing continues to grow, Informix addresses this demand with its hybrid architecture, which minimizes administrative overhead while maintaining a small memory footprint and providing substantial functionality. It is particularly adept at supporting multi-tiered architectures that require data processing across different levels, including devices, gateways, and cloud infrastructures. Additionally, Informix features native encryption to protect data both at rest and during transmission. Its support for flexible schemas, along with various APIs and configurations, further enhances its versatility, making Informix a fitting solution for contemporary data management challenges. The combination of these attributes positions Informix as a leading contender in the database landscape, capable of meeting the evolving needs of businesses and developers alike.

Easily manage complex models with ArcadeDB without compromising on performance. There's no need to rely on Polyglot Persistence; you can store various data types without using multiple databases. In one ArcadeDB Multi-Model database, you can efficiently integrate graphs, documents, key-value pairs, and time series data seamlessly. Since each model is built directly into the database engine, worries about translation delays are a thing of the past. Designed with cutting-edge technology, ArcadeDB can handle millions of records per second effortlessly. A remarkable feature of ArcadeDB is its consistent traversal speed, which remains stable regardless of the database's size, whether it contains a handful of entries or billions. Additionally, ArcadeDB can function as an embedded database on a single server but is also capable of scaling across multiple servers with Kubernetes. Its adaptable nature allows it to run on any platform while using minimal resources. The security of your data is critical; our robust, fully transactional engine ensures durability for essential production databases. To maintain consistency across different servers, ArcadeDB utilizes a Raft Consensus Algorithm, guaranteeing that your data stays reliable and synchronized even in distributed settings. With ArcadeDB, you can effectively manage all your data requirements without the complications of handling multiple systems, ensuring a streamlined and efficient experience. Whether for small projects or large-scale applications, ArcadeDB provides the flexibility and performance needed to meet diverse data challenges.

Effortlessly transform your embeddings using a single, robust tool designed for simplicity and efficiency. Explore a comprehensive database engineered to provide embedding functionalities that once required multiple platforms, thus streamlining the enhancement of your machine learning projects with Embeddinghub. Embeddings act as compact numerical representations of various real-world entities and their relationships, depicted as vectors. They are typically created by first defining a supervised machine learning task, often known as a "surrogate problem." The main objective of embeddings is to capture the essential semantics of their source inputs, enabling them to be shared and utilized across different machine learning models for improved learning outcomes. With Embeddinghub, this entire process is not only simplified but also remarkably intuitive, allowing users to concentrate on their primary tasks without the burden of excessive complexity. Furthermore, the platform empowers users to achieve superior results in their projects by facilitating quick access to powerful embedding solutions.

Apache Phoenix effectively merges online transaction processing (OLTP) with operational analytics in the Hadoop ecosystem, making it suitable for applications that require low-latency responses by blending the advantages of both domains. It utilizes standard SQL and JDBC APIs while providing full ACID transaction support, as well as the flexibility of schema-on-read common in NoSQL systems through its use of HBase for storage. Furthermore, Apache Phoenix integrates effortlessly with various components of the Hadoop ecosystem, including Spark, Hive, Pig, Flume, and MapReduce, thereby establishing itself as a robust data platform for both OLTP and operational analytics through the use of widely accepted industry-standard APIs. The framework translates SQL queries into a series of HBase scans, efficiently managing these operations to produce traditional JDBC result sets. By making direct use of the HBase API and implementing coprocessors along with specific filters, Apache Phoenix delivers exceptional performance, often providing results in mere milliseconds for smaller queries and within seconds for extensive datasets that contain millions of rows. This outstanding capability positions it as an optimal solution for applications that necessitate swift data retrieval and thorough analysis, further enhancing its appeal in the field of big data processing. Its ability to handle complex queries with efficiency only adds to its reputation as a top choice for developers seeking to harness the power of Hadoop for both transactional and analytical workloads.

Utilize Valentina DB, MySQL, MariaDB, PostgreSQL, and SQLite for free to explore, create, and manage databases. Generate detailed business reports using Valentina Studio Pro, either hosted on Valentina Server or within an application leveraging an Application Developer Kit. Implement both backward and forward engineering practices in Valentina Studio Pro, enabling the production of diagrams from existing databases and the seamless integration of new components. Craft SQL queries with enhanced features like auto-completion and syntax highlighting while effortlessly managing favorite queries and accessing recent ones. Take advantage of a function browser that offers a comprehensive dictionary for SQL functions, along with consoles that display errors, warnings, and performance insights. Efficiently search and export records in formats such as CSV, JSON, and Excel, while also modifying the properties of various database objects simultaneously. With remarkable speed, dive into tables and fields, while managing user and group privileges effectively. This comprehensive suite of tools empowers users to streamline database management processes, enhancing both productivity and accuracy. Additionally, the collaborative features encourage teamwork and knowledge sharing among users, making database management an even more integrated experience.

SAP HANA is a cutting-edge in-memory database that efficiently manages both transactional and analytical workloads by utilizing a single data copy, regardless of its nature. It effectively eliminates the divide between transactional and analytical functions within businesses, allowing for quick decision-making whether used in a traditional data center or through cloud services. This advanced database management system grants users the ability to develop intelligent, real-time applications, which promotes fast decision-making from a consolidated data repository. By integrating sophisticated analytics, it bolsters the performance of modern transaction processing systems. Organizations can leverage cloud-native features such as enhanced scalability, speed, and performance to create comprehensive data solutions. With SAP HANA Cloud, businesses gain access to dependable and actionable insights from a unified platform while maintaining stringent security, privacy, and data anonymization that align with established enterprise standards. In the rapidly evolving market landscape, the intelligent enterprise increasingly depends on prompt insights generated from data, highlighting the necessity for real-time access to critical information. As organizations face rising expectations for immediate insights, adopting a powerful database solution like SAP HANA is essential for maintaining a competitive edge. The ability to make informed decisions based on real-time data is becoming a key differentiator in business success.

Couchbase sets itself apart from other NoSQL databases by providing an enterprise-level, multicloud to edge solution that is packed with essential features for mission-critical applications, built on a platform known for its exceptional scalability and reliability. This distributed cloud-native database functions effortlessly within modern, dynamic environments, supporting any cloud setup, from customer-managed to fully managed services. By utilizing open standards, Couchbase effectively combines the strengths of NoSQL with the familiar aspects of SQL, which aids organizations in transitioning smoothly from traditional mainframe and relational databases. Couchbase Server acts as a flexible, distributed database that merges the relational database advantages, such as SQL and ACID transactions, with the flexibility of JSON, all while maintaining high-speed performance and scalability. Its wide-ranging applications serve various sectors, addressing requirements like user profiles, dynamic product catalogs, generative AI applications, vector search, rapid caching, and much more, thus proving to be an indispensable resource for organizations aiming for enhanced efficiency and innovation. Additionally, its ability to adapt to evolving technologies ensures that users remain at the forefront of their industries.

Neo4j's graph platform is crafted to enable users to maximize the potential of data and its interconnections. By utilizing Neo4j, developers can build smart applications capable of navigating the vast, interconnected datasets of today in real-time. This platform features a native graph storage engine coupled with a processing engine that enhances its capabilities. Furthermore, it offers distinctive, actionable insights through a user-friendly, adaptable, and secure database environment, making it an essential tool for modern data analysis.

This is a robust, easily scalable embedded SQL database that allows access from any location. Additionally, it offers top-tier data protection, disaster recovery solutions, synchronization of changes, and comprehensive data security measures.