milvus-io/milvus Alternatives

choose for a Rust-native vector DB with payload filtering and a simpler single-node deployment, but less cloud-native scale than Milvus.

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

choose if you need a built-in GraphQL API and object storage along with vectors, offering a more app-friendly schema.

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.

choose for a unified hybrid search (dense, sparse, full-text) with SQL-like interface if you want one engine for LLM data.

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.

choose for a multi-model SQL-based search database that can handle vectors and structured data in one engine.

The AI-Native Search Database. Best for agent storage, it unifies vector, text, structured, and semi-structured data into a single engine. This all-in-one database makes agents smarter, easier to run, and more stable.

choose when you need a full search platform with ranking, text, and vector search in one distributed system.

The AI search platform

choose for an in-process lightweight vector DB when you don't need a server, at the cost of true distributed scale.

A lightweight, lightning-fast, in-process vector database

choose for an embedded multimodal retrieval library with easy local/edge deployment, rather than a standalone server.

Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.

choose when you already live in Postgres and want basic vector search without introducing a new database service.

Open-source vector similarity search for Postgres

choose as a performance-boosting extension for pgvector inside Postgres when existing pgvector is too slow.

Postgres extension for vector search (DiskANN), complements pgvector for performance and scale. Postgres OSS licensed.

choose for a Postgres distribution with integrated full-text and vector retrieval, but AGPL licensing and Postgres scalability limits apply.

One Postgres for your application data, full-text search, vector retrieval, and aggregations. Home of the pg_search extension.

choose for a tiny embedded search engine with vectors and full-text in the browser or edge, offering low-latency on small datasets.

🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.

choose for a lightweight full-text search engine with hybrid vector support, if your primary need is search over text and vectors with a simple API.

A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.

choose for a graph+vector OLTP database on object storage if you need relationships with vectors, rather than pure vector ANN scale.

HelixDB is an OLTP graph-vector database built in Rust on Object Storage.

choose when you already run Redis and need in-memory vector similarity, but capacity and recall are limited compared to Milvus.

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.