Data Infrastructure

SurrealDB

Multi-model database combining documents, graph, relational and vector data

About SurrealDB

SurrealDB develops a multi-model database that handles relational, document, graph, time series and vector data through its own SurrealQL query language. It can run embedded, self-hosted or as the managed Surreal Cloud. It targets developers building applications and AI agents that need several data models in one engine.

Common use cases

  • Application backends
  • AI agent memory
  • Knowledge graphs
  • Real-time apps

Products and services

SurrealDB

Open source multi-model database.

Surreal Cloud

Managed database service.

Surrealist

Visual management and query tool.

Key features

  • Multi-model data
  • SurrealQL
  • Graph relations
  • Vector search
  • Real-time queries
  • Embedded mode

Integrations

  • Rust
  • JavaScript
  • Python
  • Kubernetes
  • LangChain

SurrealDB alternatives

FAQs

What is SurrealQL?

Its SQL-like query language covering relational, document and graph queries.

Is it open source?

Yes, with a managed cloud service.

Does it support vectors?

Yes.

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