Weaviate
- About
- Open-source vector database for scalable machine learning applications. Open-source alternative to Pinecone.
- Catalogue
- No. 033
- Category
- Development
- Founded
- 2017, Netherlands
- GitHub stars
- ★ 16.9k

Overview
Weaviate is an open-source vector database that allows you to store data objects and vector embeddings from your favorite ML-models, and scale seamlessly into billions of data objects. It offers a GraphQL-API and RESTful API for easy integration and supports various vectorization modules for text, images, and more.
What it does well
Weaviate provides efficient storage and retrieval of vector embeddings, making it ideal for machine learning applications. It supports multi-modal data, offers flexible querying through GraphQL and REST APIs, and includes built-in vectorization modules. Weaviate also features automatic backups, data replication, and horizontal scaling to ensure data safety and performance at scale.
Why it’s in the collection
Weaviate stands out for its versatility and scalability in the vector database space. It's designed to handle complex data structures and large-scale machine learning applications efficiently. The combination of its open-source nature, powerful querying capabilities, and support for multiple data types makes it an excellent choice for developers working on advanced AI and ML projects.
On GitHub
- Stars
- 16,883
- Forks
- 1,421
- Commits
- 30,926
- Repository
- weaviate/weaviate
Languages
- Go 97.1%
- Python 0.5%
- Other 3.4%
Compared with
PineconeCloud-native vector database, but not open-source and potentially more expensive for large-scale use.
MilvusAnother open-source vector database, but with a different architecture and feature set.
ElasticsearchPopular search engine that can be used for vector search, but not primarily designed for this purpose.



