Question: Can you recommend a cloud-native vector search engine that supports zero-downtime upgrades and horizontal scaling?

If you're looking for a cloud-native vector search engine that supports zero-downtime upgrades and horizontal scaling, Qdrant could be the way to go. It's an open-source vector database and search engine designed for fast and scalable vector similarity searches. Qdrant is designed for cloud-native architecture and supports high-availability with ease of use and simple deployment via Docker. It also offers flexible pricing plans, including Qdrant Cloud, Hybrid Cloud, and Private Cloud, and is available on major cloud marketplaces.

Another great option is Pinecone. Pinecone is a serverless vector database designed for fast querying and retrieval of similar matches across billions of items. It supports real-time updates and hybrid search that combines vector search with keyword boosting. Pinecone offers a range of pricing plans, including a free starter plan, and integrates with major cloud providers, making it a scalable and cost-effective option for a range of use cases.

If you're looking for something more comprehensive, Elastic has a powerful Search AI Platform that combines search and artificial intelligence to help you extract insights from massive amounts of data. It includes vector search along with other features like generative AI and security analytics. Elastic serves many industries and offers flexible pricing models, so it can accommodate a range of business needs.

Last, Vespa is another powerful platform that combines vector search with lexical search and structured data search. It supports scalable and efficient machine-learned model inference and is designed to build production-ready search applications at any scale. Vespa offers free usage to get started, so developers can quickly apply AI to their data and build high-performance applications.