Weaviate
Weaviate is an open-source vector database designed to store and manage both objects and vectors, enabling combined vector search with structured filtering. It offers fault tolerance, scalability, and is built as a cloud-native, developer-friendly solution for semantic search and AI-powered applications.
Weaviate is built in Go, distributed under the BSD 3-Clause "New" or "Revised" License, 16.0k GitHub stars from 100 contributors, latest release v1.36.10.
When to use Weaviate
Weaviate is listed here as a Database project. The directory calls out Vector-based similarity search, Combines structured and unstructured data, Scalable and cloud-native architecture as capabilities associated with it.
Other recorded traits for Weaviate include Fault tolerance for reliability, Supports semantic search and hybrid queries.
Besides Database, this page also files Weaviate under AI, Development, Web.
Weaviate compared with
Records in this directory name Pinecone, Milvus, Qdrant, Chroma as products people compare with Weaviate. That list is editorial metadata, not a claim that Weaviate replaces each of them.
Open-source projects that mention Weaviate are collected on a separate alternatives page.
What the Weaviate stats reflect
GitHub currently shows 16.0k GitHub stars, about 100 contributors, 1.3k forks, 543 open issues, latest tracked release v1.36.10. Star and activity counts here are a snapshot used as a proxy for community adoption, not a quality score.
Stats refreshed
- Language
- Go
- Latest Release
- v1.36.10
- License
- BSD 3-Clause "New" or "Revised" License
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Key features of Weaviate
- Vector-based similarity search
- Combines structured and unstructured data
- Scalable and cloud-native architecture
- Fault tolerance for reliability
- Supports semantic search and hybrid queries
See open-source alternatives to Weaviate
Compare with
Weaviate resources
Weaviate on GitHub
Frequently asked questions
What is Weaviate?
Weaviate is an open-source vector database designed to store and manage both objects and vectors, enabling combined vector search with structured filtering. It offers fault tolerance, scalability, and is built as a cloud-native, developer-friendly solution for semantic search and AI-powered applications. This directory highlights Vector-based similarity search, Combines structured and unstructured data, Scalable and cloud-native architecture.
Is Weaviate free to use?
Weaviate is published as open source under the BSD 3-Clause "New" or "Revised" License. The directory lists Vector-based similarity search, Combines structured and unstructured data, Scalable and cloud-native architecture among its recorded capabilities.
What language is Weaviate written in, and what is the latest release?
Weaviate is written primarily in Go. The latest release tracked on this page is v1.36.10.
How widely is Weaviate used on GitHub?
Weaviate has about 16.0k GitHub stars across about 100 contributors. It also has about 1.3k forks. Those counts are a snapshot of community attention, not a ranking of quality.
What do people compare Weaviate with?
This directory records Pinecone, Milvus, Qdrant, Chroma as comparison points for Weaviate. A longer list of open-source projects that mention Weaviate is at https://www.open-source-tools.com/alternatives/weaviate.
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