SurrealDB
Open SourceFundedUnified multi-model database platform for AI agents and real-time applications
About SurrealDB
SurrealDB is an advanced multi-model database platform designed to unify documents, graphs, vectors, time-series, and relational data into a single, strongly consistent transactional system. It eliminates the complexity of stitching together multiple specialized databases by providing one query language, one transaction boundary, and one deployment model. This platform is particularly suited for enterprises building AI agents, real-time applications, knowledge graphs, and embedded or edge solutions that require reliable context and memory management.
Targeted at enterprise organizations across industries such as finance, healthcare, gaming, and manufacturing, SurrealDB offers scalable, horizontally distributed storage with compute-storage separation and object storage compatibility. Its unique architecture integrates persistent agent memory and context layers, enabling AI agents to reason over consistent, queryable history without the need for separate memory middleware. This reduces latency, operational overhead, and failure modes associated with managing multiple data systems, delivering a robust foundation for AI-driven intelligent systems.
Key Capabilities
- ✓Multi-model support for documents, graphs, vectors, and time-series
- ✓Single ACID transaction across all data models
- ✓Persistent, queryable agent memory for AI applications
- ✓Horizontally scalable distributed storage with quorum consensus
- ✓Unified query language and permission model
Integrations
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