Open Source Vector Databases Software
Vector Databases store and index high-dimensional embeddings to enable similarity searches across unstructured data. These tools allow for the retrieval of information based on semantic meaning rather than exact keyword matches. This type of software is for developers building recommendation systems or retrieval augmented generation workflows. Self-hosting these apps ensures that sensitive embedding vectors and metadata remain on private infrastructure. This approach prevents the need to send proprietary data to external API providers for vector indexing and retrieval.
This page lists 3 open source tools in the Vector Databases category. The most popular are Milvus, Qdrant and Databend. Most use the Apache-2.0 or Custom license, and 3 offer an official Docker image.
Milvus
A distributed vector database for organizing and searching unstructured data through similarity search and metadata filtering.
Qdrant
Store and search vector embeddings with integrated payload filtering for semantic search and recommendation systems.
Databend
An open-source cloud data warehouse for large-scale analytics, vector search, and full-text search using Rust.
Join our newsletter to get shiny new open source software delivered to your inbox. Unsubscribe anytime.