Question: Is there a vector database that allows real-time updates and hybrid search with keyword boosting for more accurate results?

If you're looking for a vector database that supports real-time updates and hybrid search with keyword boosting for more accurate results, Pinecone is an excellent choice. Pinecone offers fast querying and retrieval of similar matches across billions of items in milliseconds. It supports real-time updates, low-latency vector search, metadata filtering, and hybrid search that combines vector search with keyword boosting. This makes it ideal for applications that require scalable and efficient search capabilities.

Another noteworthy option is Trieve. Trieve provides a full-stack infrastructure for building search, recommendations, and RAG (Retrieval-Augmented Generation) experiences. It supports private managed embedding models, semantic vector search, and hybrid search, which is suitable for advanced search capabilities like date recency biasing and re-ranker models. Trieve also supports merchandising relevance tuning and offers a free plan for non-commercial use, making it accessible for developers.

Vespa is another versatile platform that combines vector search with lexical search and search in structured data. It supports scalable and efficient machine-learned model inference and offers a unified search engine that can handle various data types in a single query. Vespa is particularly useful for building production-ready search applications at any scale and integrates well with a variety of machine learning tools.

For an open-source solution, Qdrant offers a cloud-native vector database and search engine that focuses on fast and scalable vector similarity searches. It provides high-performance processing of high-dimensional vectors and integrates with leading embeddings and frameworks. Qdrant supports deployment on both local and cloud options, including a free tier, and offers flexible pricing plans for different use cases.