Open-source AI Tools
SurrealDB

An innovative multi-model database combining document, graph, relational, and vector search features into one platform.

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Use Case
Developing complex web apps needing connected graph relations, traditional relational data, and integrated vector search capabilities.
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SurrealDB is an innovative, next-generation multi-model database designed to collapse backend infrastructure complexity. It uniquely combines the features of document databases, relational databases, graph databases, and vector search engines into a single unified platform, eliminating the need to maintain multiple distinct databases for complex data paradigms.

SurrealDB allows developers to perform real-time data analysis, write complex graph relations, handle structured documents, and manage vector embeddings using a powerful SQL-like query language called SurrealQL. It supports flexible deployments, working as an embedded library, a single-node database, or a highly distributed cloud system. With built-in user authentication and permissions, it can even act as a secure backend service connected directly from web browsers.

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