The top 12 open-source databases in 2025

What is open source database software?

An open-source database system is a redistributable, downloadable codebase that's free to use. Developers can build custom database applications using its built-in features, tailoring them to meet their organization’s specific needs.

Typically, databases are classified as either relational or non-relational (NoSQL).

• Relational databases (SQL databases) store structured data in columns and rows using key-value pairs.
• Non-relational databases (NoSQL databases) use various data storage architectures to manage both structured and unstructured data.

Open-source solutions let developers monitor and manage data on their own terms, allowing them to create a customized system tailored to their exact business needs.

Top 12 open source databases in 2025

There are several open-source database solutions to choose from.

1. MySQL

MySQL is known for its reliability and strong performance in ecommerce, web, and online transaction processing (OLTP) systems. Created in 1994 in Sweden, MySQL is now maintained by Oracle and remains a core component of the LAMP stack (Linux, Apache, MySQL, PHP/Python/Perl).

Key benefits:

• Fully ACID-compliant with InnoDB as the default storage engine.
• High availability through automatic failover and group replication with InnoDB Cluster.
• Built-in security features like Transparent Data Encryption (TDE) and Enterprise Firewall.
• Advanced SQL support, including window functions, CTEs, and invisible indexes for cleaner queries.
• Broad cloud support across AWS, Google Cloud, and Azure.

MySQL is best suited for applications that require fast and consistent access to structured data, such as websites, CMSs, online stores, and SaaS products. It powers well-known platforms, including Facebook and Twitter. It isn’t designed for unstructured or large, distributed data, so if you expect massive horizontal scaling, a NoSQL option might be a better fit.

MySQL is free to use under the GPL license, with source code available on GitHub. Oracle also offers paid Enterprise editions with additional features and official support.

2. PostgreSQL

PostgreSQL, an open-source database originating from a 1980s UC Berkeley project, was released in the mid-1990s. Its support for ACID compliance and complex data types has led to its wide adoption in web development, GIS (with PostGIS), financial services, e-commerce, and analytics.

• Supports both structured (tables) and semi-structured (JSON, arrays) data for flexible storage.
• Scales horizontally across multiple machines and vertically on a single server to handle growing workloads.
• Works with most standard programming languages and is fully compatible with SQL. It also integrates with many third-party tools, including Fivetran.
• Offers table partitioning and indexing options for faster queries on large datasets.
• Provides asynchronous replication and automatic failover for reliability and business continuity.
• Extensible through custom data types, plug-ins, and stored procedures, allowing deep customization.
• Known for its stability, consistency, and mature community support.

It’s not ideal for analytics or use cases that are read-heavy and do not work with strict schema.

PostgreSQL has extensive commercial and cloud support options. Along with EDB (formerly EnterpriseDB), providers like Crunchy Data, ScaleGrid, Citus Data, and ElephantSQL offer managed and enterprise-ready PostgreSQL solutions. It’s also available as a fully managed service through major cloud platforms like AWS, Google Cloud, Azure, and DigitalOcean.

3. MariaDB

MariaDB was created as a fork of MySQL by its original developer, Michael Widenius, after Oracle acquired MySQL in 2010. The goal was to preserve MySQL’s open-source spirit while continuing innovation independently.

Key benefits:

• Compatible with MySQL for most commands and tools.
• Pluggable storage engines allow teams to optimize for different workloads, from transactional to analytical.
• Uses the Galera Cluster engine for data replication and high availability.
• Supports Multi-Version Concurrency Control (MVCC), allowing many users to read and write data simultaneously.
• Enhanced JSON functions, columnar storage, and query optimizations for better flexibility and speed.

It’s ideal for organizations that need a fully open-source, drop-in replacement for MySQL with advanced clustering, analytics, and enterprise features. Although highly compatible, some MySQL extensions or functions might not work perfectly due to differences between the two projects.

MariaDB PLC offers an Enterprise Server edition with advanced capabilities, such as columnar storage and JSON support. SkySQL, a managed cloud service from MariaDB PLC, provides Database-as-a-Service (DBaaS) options.

You can explore MariaDB’s source code on GitHub.

4. MongoDB

MongoDB was released in 2009 by MongoDB Inc. as a document-oriented NoSQL database. It was designed to provide developers with more flexibility than traditional relational databases, particularly for modern, data-intensive applications.

Key benefits:

• Uses a flexible, JSON-like document model instead of fixed schemas.
• Natively supports document, graph, geospatial, and time-series data in one system.
• Includes powerful ad-hoc queries, aggregation pipelines, and multi-document ACID transactions for data integrity.
• MongoDB Atlas, its managed cloud platform, adds vector and full-text search capabilities, with free options for local development and testing.
• Offers built-in replication and automated backups to ensure high availability and disaster recovery.

It’s best for developers building applications that need flexibility in data structure for real-time analytics, content management, IoT, or AI-driven systems.

It doesn’t support traditional SQL joins, so complex relationships may require manual data modeling or denormalization.

MongoDB Inc. provides enterprise support through MongoDB Enterprise Advanced and offers managed hosting with MongoDB Atlas across AWS, Google Cloud, and Azure.

On the open-source side, MongoDB’s core was historically open source. But since 2018, it has been under the Server Side Public License (SSPL), which differs from traditional open-source licenses. The source code is publicly available on GitHub, but it is licensed under the SSPL, which restricts commercial use and linking.

MongoDB’s source code is publicly available on GitHub.

5. SQLite

SQLite was first released in 2000 by D. Richard Hipp. It was designed to be a simple, reliable, and lightweight database that could run inside applications without needing a separate server.

Key benefits:

• Serverless and self-contained, no setup or configuration required.
• Stores the entire database in a single file, making it easy to move or back up the database.
• Very small in size (less than 500 KB) but supports powerful SQL features like JSON functions, multi-column indexes, and virtual tables.
• Works across platforms and programming languages, making it easy to embed in apps.

Best for developers building apps that need simple, local storage, like mobile apps, small websites, desktop tools, or a medium-sized content management system (CMS). It’s not ideal for large, high-traffic systems or multi-user environments that need advanced features like clustering or concurrent writes.

The SQLite source code is free to use and distribute without a license. There are also options for paid technical support, testing, and custom builds.

6. CockroachDB

CockroachDB was born in 2015 from the engineers at Cockroach Labs who wanted to build a SQL database that could survive major failures and scale across the globe. It draws inspiration from systems like Google Spanner to bring together the familiar world of SQL with the resilience and distribution of cloud-native architecture.

Key benefits:

• Full ACID transactions with strong consistency across nodes.
• Automatically scales horizontally.
• Built-in high availability ensures that if a server, rack, or data center fails, CockroachDB stays operational.
• “Multi-active availability” means every node can accept reads and writes, so your app stays responsive even when parts of the infrastructure are down.
• Geo-partitioning and data placement control capabilities.
• Compatible with PostgreSQL’s wire protocol and many SQL commands, making migration and tooling easier.

It’s ideal for critical applications that must be up and responsive at all times, span multiple regions or clouds, and handle large volumes of transactions.

But it is more complex, requires careful design, and is more costly to run.

Since 2019, CockroachDB has used a mixed licensing model. Most core features fall under the Business Source License (BSL), which becomes fully open source (Apache 2.0) after 3 years. Others are under the Cockroach Community License (CCL), which allows full use and modification but not commercial resale.

Cockroach Labs also has paid enterprise features and support for both self-hosted and managed (DBaaS) deployments.

7. Redis

Redis, short for "Remote Dictionary Server”, was first released in 2009 by Salvatore Sanfilippo as an in-memory key-value store.

Key benefits:

• Stores all data in memory for fast read/write operations.
• Supports multiple data types like strings, lists, sets, sorted sets, and hashes.
• Works with more than 50 programming languages.
• Module API to build custom extensions for adding new data types or behaviors.
• Offers optional persistence to disk so data can survive restarts or crashes.

Redis is best for developers building fast, data-driven systems such as caching layers, real-time analytics, leaderboards, message queues, and chat or gaming backends.

As of 2025, Redis uses a tri-license model comprised of:

• Redis Source Available License (RSALv2);
• Server Side Public License (SSPL); and
• GNU AGPLv3.

The Redis source code remains publicly available on GitHub.

8. CouchDB

CouchDB was first released in 2005 and is maintained by the Apache Software Foundation. It’s a NoSQL document database built for reliability, offline syncing, and easy replication across devices and networks.

Key benefits:

• Stores data as flexible JSON documents.
• Uses MVCC to prevent conflicts during concurrent writes.
• Provides master-master replication and incremental syncing for offline-first or distributed use cases.
• Offers a simple RESTful HTTP API that works well with web, mobile, and IoT apps.
• Supports clustering for scaling across multiple nodes and maintaining high availability.
• Ideal for apps that need reliable synchronization during poor connections, minimizing data loss in unstable network conditions.

However, if your only goal is large-scale database replication, tools like Fivetran offer more efficient managed replication pipelines.

CouchDB is fully open-source and distributed under the Apache License 2.0, allowing unrestricted use, modification, and distribution for both personal and commercial projects. The source code is available publicly on the Apache CouchDB GitHub repository.

9. Neo4j

Neo4j is a graph database released in 2007 that stores data as nodes and relationships, not in tables with rows and columns.

Each node represents an entity, and each relationship connects nodes to form a web-like structure. This approach makes it much easier to model and query complex, highly interconnected data.

Key benefits:

• Changes to data models are easy and non-disruptive, supporting evolving business needs.
• The Cypher query language allows expressive and readable queries for complex graph patterns.
• Built-in ACID compliance ensures reliable and consistent transactions.
• Scalable for large datasets in enterprise environments and supports clustering for high availability.

Use cases revolve around applications that need to model, analyze, or traverse connections, like social networks, recommendation engines, fraud detection, supply chain optimization, knowledge graphs, and identity or access management.

Neo4j’s core “Community Edition” is released under an open-source, modified GPLv3 license, but it lacks features like clustering and advanced backup, which are reserved for the commercial “Enterprise Edition”.

The full source code for the Community Edition is available on GitHub.

10. FirebirdSQL

FirebirdSQL originated from Borland’s InterBase in the early 2000s and is a lightweight yet full-featured relational DBMS.

Key benefits:

• Supports standards-compliant SQL, including many ANSI SQL features, triggers, stored procedures, and views.
• Its multi-generational architecture enables high concurrency without locking issues, allowing simultaneous OLTP and OLAP operations.
• Reliable transaction support, good query optimization, and robust performance in small and medium-scale deployments.

It’s ideal for embedded databases in desktop tools (such as LibreOffice Base) or mobile applications, as well as situations that require efficient, transactional relational data management.

FirebirdSQL is fully open source, released under the permissive Initial Developer’s Public License (IDPL), allowing free use, modification, and distribution for commercial and personal projects.

The official code is available on GitHub.

11. OrientDB

OrientDB was launched in 2011 as a multi-model NoSQL database that integrates graph, document, key-value, and object models in a single scalable engine.

Key benefits:

• Delivers fast performance with physical links for efficient traversals and queries, avoiding expensive joins.
• Provides ACID-compliant transactions and enables horizontal scaling.
• Offers a SQL-like query language extended for graph capabilities, making it easier for SQL users to adopt.
• Supports schema-less, schema-full, or mixed schemas depending on application needs.
• Strong security features, including role-based access control and encryption.

Use cases involve social media, recommendation systems, identity management, or other apps requiring flexible models and complex relationships.

The Community Edition is open source (Apache 2.0), with commercial support and advanced features from OrientDB Ltd, now part of SAP.

Source code is available on GitHub.

12. Cassandra

Apache Cassandra was developed at Facebook in 2007 by Avinash Lakshman and Prashant Malik to support inbox search, and it was open sourced in 2008 under the Apache Software Foundation.

Key benefits:

• Peer-to-peer distributed architecture eliminates single points of failure.
• Scales horizontally by adding nodes, supporting large datasets and high traffic.
• Tunable consistency lets you balance availability and accuracy with application needs.
• Multi-datacenter replication offers fault tolerance and provides global, low-latency access.
• Self-healing features automatically detect and fix node failures without downtime.
• Offers high write and read throughput for real-time big data operations.

Cassandra excels in scenarios involving time-series data, event logging, IoT data storage, real-time analytics, catalog and inventory systems, messaging queues, and recommendation engines, providing a resilient and scalable backbone for global applications.

It is fully open source under the Apache License 2.0. The source code repository is available on GitHub.

How to choose the right open source database software

When selecting a database solution for your team, keep these four factors in mind:

• Understand your workload: Determine what you want to use your database for. Consider the data types, query types, performance expectations, and business requirements for your organization.

• Know your use cases: Choose a database that can support multiple use cases without interruption or downtime. As business goals change frequently, so will data models and use cases. Choosing a rigid tool will force data migration to another database.

• Check for security features: Data security is a primary concern for organizations. Your database vendor must keep data safe from hackers and prevent sensitive data from being exposed during transit or at rest. Secure log-ins, encryption, role-based access control, and compliance are also important.

• Consider the cost: While many open source databases are free, most charge fees for enterprise plans and additional features. MongoDB Atlas is an example of this. Those using open-source tools also have to consider the labor and time costs of building their own database, rather than buying a fully managed platform like Amazon Redshift.

Connect your open source database with Fivetran

We have explored 12 open source databases, each bringing unique strengths. These databases help data engineers and organizations to build reliable, scalable, and customizable data solutions while controlling costs.

Whether you need traditional relational capabilities (MySQL, PostgreSQL), flexible multi-model support (OrientDB, Neo4j), or high-speed NoSQL performance (MongoDB, Cassandra), there is an open source option suited for the job.

Ultimately, the best choice depends on your project’s specific needs, workload type, and business requirements.

Fivetran’s extensive library of data connectors supports both open source databases and proprietary platforms.

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