A simple, fast, and versatile Datalog database with built-in document, vector, and full-text search capabilities.
Datalevin is a durable Datalog database that provides a simple, fast, and versatile data storage solution. It combines the declarative querying of Datalog with support for multiple data models—including key-value, document, and vector storage—while offering robust ACID transactions and high performance. It solves the problem of needing separate databases for different workloads by unifying them under a single, efficient engine.
Developers building applications that require complex querying, graph traversal, or multi-model data storage, particularly in the Clojure ecosystem. It's also suitable for AI/ML practitioners needing integrated vector search and embedding generation for RAG applications.
Developers choose Datalevin for its performance-optimized Datalog engine, which outperforms alternatives like Datomic and Datascript on complex joins, and its versatility in replacing multiple specialized databases. Its open-source nature, familiar ACID semantics, and built-in AI capabilities provide a unique all-in-one solution.
A simple, fast and versatile Datalog database
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Datalevin's cost-based query optimizer makes complex joins up to 4x faster than SQLite and 2.4x faster than PostgreSQL, as demonstrated in the JOB benchmark, due to better plan generation.
It unifies key-value storage for EDN data, a document database with automatic path indexing, and a vector database with SIMD-accelerated search, reducing the need for multiple specialized databases.
Built-in MCP server, in-database embedding, OCR, and text generation via llama.cpp enable RAG applications without external services, as highlighted in the features section.
Can be embedded like SQLite, run in client/server mode with RBAC, or used as a Babashka pod for scripting, offering adaptability across different use cases.
Datalog is less common than SQL, requiring teams to invest time in learning its declarative syntax and semantics, which can slow onboarding and limit hiring options.
Compared to established databases like PostgreSQL, Datalevin has fewer third-party tools, monitoring solutions, and community resources, increasing development overhead for integrations.
Key production features like read-only replicas, high availability, and JSON API are still on the roadmap for future versions, making it less suitable for immediate needs in these areas.
Datalevin is an open-source alternative to the following products:
Neo4j is a graph database management system that uses graph structures with nodes, edges, and properties to represent and store data.
Datomic is a distributed database designed as a composition of simple services, featuring immutable data, time travel queries, and a flexible data model that separates storage, processing, and memory.
PostgreSQL is a powerful, open-source object-relational database system with strong emphasis on extensibility and SQL compliance.