If you're looking for something besides Neo4j, Pinecone is another top contender. It's optimized for querying and retrieving similar matches from a large number of items, with a serverless design that automatically scales without you worrying about the database. Pinecone supports low-latency vector search and real-time indexing, and it's certified for enterprise use with SOC 2 and HIPAA compliance.
Another alternative is Vespa, which combines a unified search engine and vector database for a variety of search types, including lexical and structured data. Its ability to incorporate machine-learned models and perform scalable, efficient inference makes it a good choice for search, recommendation and generative AI. Vespa offers free usage to get a quick start with AI-boosted data applications.
Couchbase is another multi-tool, a NoSQL cloud database platform that accommodates a variety of data access methods, including key-value, JSON, SQL and vector search. Its memory-first architecture is designed for high performance, and it can be integrated with leading public cloud services, making it a good choice for many business needs.
If you need an open-source option, Qdrant offers a fast and scalable vector database that's designed for cloud-native designs. Built with the Rust programming language for high-performance processing, it can be used with popular embeddings and frameworks and can be deployed in a variety of ways, including a free tier, making it a good, low-cost option for use cases like advanced search and recommendation.