2 repos
Systems for storing and querying high-dimensional vector embeddings to support semantic search.
Distinguishing note: Focuses on vector-based semantic retrieval rather than general-purpose relational data storage.
Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Vector Databases. Refine with filters or upvote what's useful.
ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring. The platform distinguishes itself through ad
Provides high-performance vector search and data aggregation capabilities optimized for generative AI and machine learning workflows.
Quivr is a retrieval-augmented generation platform designed to transform raw documents into searchable knowledge bases. It functions as a centralized environment where users can ingest files, index them into vector databases, and interact with language models to receive contextually relevant, data-backed responses. The platform distinguishes itself through an agentic workflow orchestrator that sequences retrieval tasks, tool execution, and model interactions to resolve complex, multi-step queries. This engine is entirely configuration-driven, allowing users to define document ingestion, chunk
Store and retrieve vector embeddings in relational databases to enable efficient similarity searches and semantic data retrieval for large knowledge bases.