Quick answer: OSS vector DB with hybrid search + GraphQL.
Weaviate is an open-source vector database built for storing, searching, and managing high-dimensional vector embeddings at scale. Created by the Weaviate team, it enables semantic search and similarity-based queries by converting text, images, and other data into vectors and organizing them efficiently. Weaviate combines vector search with traditional keyword filtering through hybrid search capabilities, allowing you to find results based on meaning rather than just exact matches. The platform includes a GraphQL API for flexible querying and integrations with popular embedding models like OpenAI and Hugging Face. Available both as open-source for self-hosting and as a managed cloud service, Weaviate serves as a foundational layer for AI applications that require intelligent, context-aware search and retrieval.