Vector databases in 2026

Commercial vector databases

1. 1
   Pinecone Pinecone Systems

   Pinecone is the trusted AI knowledge company. Its AI knowledge platform—Database, Nexus, and Marketplace—powers accurate, fast, cost-effective AI for 10,000+ customers and 1M developers worldwide.

   Building block Production-ready You need vector search at scale in production and do not want to run the infrastructure.

   Commercial

Open-source vector databases

Frameworks and platforms to build on 2

1. 1
   LangChain4j langchain4j

   LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.

   Framework or platform Production-ready You are adding LLM features to a Java or Kotlin application and want to stay on the JVM.

   ★ 13k Apache-2.0 Java Active, pushed today
2. 2
   Txtai neuml

   💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

   Framework or platform Usable You want one Python library to build semantic search and RAG locally with few external services.

   ★ 13k Apache-2.0 Python Active, pushed today

Building blocks for your own system 8

1. 1
   Milvus milvus-io

   Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

   Building block Production-ready You need vector search over hundreds of millions of embeddings or more and have the people to run a distributed system.

   ★ 47k Apache-2.0 Go Active, pushed today
2. 2
   Qdrant qdrant

   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/

   Building block Production-ready You are building semantic search, RAG or recommendations and want a dedicated vector store that is simple to self-host.

   ★ 35k Apache-2.0 Rust Active, pushed today
3. 3
   Cognee topoteretes

   Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory with small models for free

   Building block Usable You build agents that need long-term memory across sessions and want graph-based retrieval rather than plain vector RAG.

   ★ 33k Apache-2.0 Python Active, pushed today
4. 4
   Chroma chroma-core

   Search infrastructure for AI

   Building block Production-ready You are building retrieval for an LLM app and want something simple to start with locally.

   ★ 30k Apache-2.0 Rust Active, pushed 3 days ago
5. 5
   Zvec alibaba

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

   Building block Usable You want SQLite-style embedded vector search inside an app or agent without a separate server.

   ★ 16k Apache-2.0 C++ Active, pushed today
6. 6
   LEANN StarTrail-org

   [MLsys2026 Best Paper]: https://arxiv.org/abs/2506.08276. RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.

   Building block Experimental You want to search your own files, email or chat history with RAG on a laptop and storage is the constraint.

   ★ 14k MIT Python Active, pushed yesterday
7. 7
   LanceDB lancedb

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

   Building block Usable You want serverless vector search embedded in a Python, TypeScript or Rust app, with data kept in files on S3 or disk.

   ★ 12k Apache-2.0 Rust Active, pushed today
8. 8
   OceanBase oceanbase

   OceanBase is the unified distributed database for the AI era — open-source, multi-model, one engine for your most demanding workloads.

   Building block Production-ready You need a scale-out MySQL-compatible database with high availability, especially in finance or large Chinese enterprise settings.

   ★ 10k Apache-2.0 C++ Active, pushed 3 days ago

All 30 open-source vector database projects

Compared head to head

Also under databases

Open-source licenses

• Permissive: 26. Use it anywhere, including in closed products. You keep the copyright notice; Apache-2.0 also grants patent rights.
• Network copyleft: 3. Like GPL, and running a changed version as a web service counts as distributing it, so its users get the source too.
• Strong copyleft: 1. If you distribute the program or anything built on it, you must release the whole source under the same license.

Languages

Rust 7, Python 6, C++ 5, TypeScript 5, Java 3, Jupyter Notebook 2, Go 1 and PHP 1.