
A new standard for NoSQL emerges as Microsoft open-sources DocumentDB, bringing PostgreSQL-powered document database capabilities with built-in vector search to developers.
In a significant move that could reshape the landscape of document databases, Microsoft has announced the open-source release of DocumentDB, the engine powering Azure Cosmos DB for MongoDB. This strategic initiative, built on PostgreSQL, aims to address long-standing challenges in the NoSQL database ecosystem while leveraging the growing popularity of PostgreSQL among developers.
The announcement marks a shift in how enterprises can approach document database implementations. By open-sourcing DocumentDB under the MIT license, Microsoft is providing developers with a powerful, production-ready local instance of a document data store and taking steps toward establishing an industry standard for NoSQL databases—similar to what ANSI SQL achieved for relational databases.
At its core, DocumentDB consists of two primary components: pg_documentdb_core, a custom PostgreSQL extension optimizing BSON datatype support, and pg_documentdb_api, which handles CRUD operations, query functionality and index management. This architecture enables developers to leverage PostgreSQL’s robust feature set while maintaining the flexibility and scalability benefits traditionally associated with NoSQL solutions.
“The NoSQL landscape has historically been fragmented, with cloud-specific solutions lacking a common standard for interoperability,” notes Abinav Rameesh, Principal PM Manager of Azure Cosmos DB. “DocumentDB addresses this challenge head-on, providing complete visibility into the architecture and implementation of the engine.”
The timing of this release is particularly relevant as organizations increasingly adopt AI and machine learning technologies. DocumentDB’s vector search capabilities, powered by the pg_vector PostgreSQL extension, support various use cases including generative AI applications, chatbots, fraud detection and recommendation systems. This functionality positions DocumentDB as a versatile solution for both traditional document storage and emerging AI-driven applications.
For developers already working with document databases, the transition path is streamlined through FerretDB 2.0, which uses DocumentDB as its backing engine. This integration provides a familiar document database protocol interface while benefiting from DocumentDB’s PostgreSQL foundation.
Key Features and Benefits:
- Full BSON document support with nested document manipulation
- Comprehensive indexing capabilities, including single-field, multi-key, compound, text and geospatial indexes
- Vector search functionality for AI and machine learning applications
- SCRAM authentication mechanism for secure access
- MIT license offers complete freedom to use, modify and distribute
- Built on PostgreSQL, leveraging its mature ecosystem and extensive feature set
The open-source nature of DocumentDB, combined with its permissive MIT license, enables developers to incorporate the project into their solutions without commercial licensing fees or usage restrictions. This approach aligns with modern development practices while providing the flexibility needed for custom implementations.
Looking ahead, Microsoft’s vision extends beyond just providing another database option. The company aims to establish DocumentDB as the foundation for a standardized approach to NoSQL databases, simplifying how organizations manage and migrate between different document database solutions.
For IT leaders and developers interested in DocumentDB, the project is available on GitHub with comprehensive documentation and a straightforward Docker-based setup process. The active Discord community provides direct access to the project’s creators and fellow developers, fostering collaboration and knowledge sharing.
This initiative represents a significant step forward in database technology, offering organizations a robust, standards-based approach to document database implementation while maintaining modern applications’ flexibility and scalability requirements. As the project evolves, it could become a cornerstone of future NoSQL database implementations across the industry.