CozoDB
General-purpose, transactional, relational-graph-vector database that uses Datalog for queries. Embeddable but capable of handling large amounts of data and concurrency with HNSW indices for high-performance vector similarity searches.
About this tool
Overview
CozoDB is a unique database that combines relational, graph, and vector capabilities in a single system using Datalog as its query language. Starting from version 0.6, it includes vector search capabilities using HNSW indices.
Features
- Multi-Model: Combines relational, graph, and vector data models
- Datalog Queries: Powerful declarative query language
- Vector Search: HNSW-based similarity search since v0.6
- Embeddable: Can run embedded in applications
- Transactional: Full ACID transaction support
- Scalable: Handles large datasets and high concurrency
- Graph Analytics: Native support for graph algorithms
- Time Travel: Built-in temporal queries
Use Cases
- Knowledge graph applications with vector embeddings
- Complex graph analytics with semantic search
- Applications requiring combined relational and vector queries
- Embedded AI applications
Query Language
Uses Datalog, a declarative logic programming language that's particularly powerful for graph queries and recursive operations.
Integration
Can be embedded in Rust, Python, NodeJS, Java and C applications. Works well for AI applications requiring both structured and vector data.
Pricing
Free and open-source under MPL-2.0 license.
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