Weaviate Systemeigenschaften

• High performance – typically performs a 10-NN neighbor search out of millions of objects in single-digit milliseconds.
• Extensible, built-in machine learning (ML) modules –  Modules enable use of popular services and model hubs such as OpenAI, Cohere or HuggingFace and much more to vectorize data and perform generative AI operations for any data type or use case.
• Rich vector search – Supports a variety of ML searches with the added benefit of being able to search vectors AND the source objects from which the vectors were generated.
  
• Production ready - Built with scaling, replication, multi-tenancy, and security in mind.
  

• Flexible deployment - Free, open source or fully-managed cloud vector database service
  
• Stores vectors AND source objects together - simplifies development by eliminating the need to host and integrate separate databases for source objects and their vectors. 
  
• Extensible modules architecture - intergrates with a variety of machine learning models from OpenAI, Cohere, HuggingFace, Google, and others to provide native vectorization and generative AI (results transformation) capabilities.

All companies that have data. ​

As of mid 2023:

• Over 2 million open source downloads
  
• 3500+ Weaviate Slack community members - https://weaviate.io/slack
• 6800 stars on Github - https://github.com/weaviate/weaviate

• Weaviate is open-source, and free to use.
  
• Weaviate is also available as a fully managed cloud vector database service, with prices starting at $25 per month - details are here: https://weaviate.io/pricing