Supabase Vector

Supabase Vector is an open-source, Postgres Vector database and AI Toolkit integrated with Supabase. It allows developers to store, index, and access embeddings using pgvector and build AI applications using Supabase's AI toolkit.

Key Features

• Postgres + pgvector: Store, query, and index vector embeddings in a Postgres instance, enabling users to leverage the power of SQL for vector operations.
• OpenAI and More: Easily connect to any LLM or embeddings API, including Hugging Face and SageMaker, allowing developers to seamlessly integrate OpenAI models into their applications.
• Secure and Scalable: Supabase Vector is SOC2 Type 2 compliant, ensuring data security, and bietet a scalable architecture that can handle large volumes of vector data.

Use Cases

• Build semantic search engines that enable users to search for content based on semantic similarity.
• Enhance chatbots with content-based long-term retention, allowing them to recall and respond to previous conversations.
• Develop image similarity applications that can recognize and cluster similar images based on visual features.

Conclusion

Supabase Vector provides a robust and accessible platform for developing AI applications, enabling developers to store, query, and index vector embeddings seamlessly within Postgres. Its integration with Supabase ensures security, scalability, and ease of use, making it a valuable tool for building a wide range of AI-powered applications.