Question: Can you suggest a platform that supports multiple data models, including JSON, time-series, and full-text search, for building modern SaaS applications?

If you're looking for a platform that can handle multiple data models, including JSON, time-series and full-text search, SingleStore is a good option. It's a real-time data platform for intelligent applications with high-throughput streaming data ingestion and millisecond query performance. It can handle multiple data models, including JSON, time-series, vector, geospatial and more in one engine, which is good for SaaS apps. The platform also offers flexible scaling with read replicas and separate storage and compute, with pricing starting at $0.90/hr for the standard tier.

Another good option is Couchbase, a NoSQL cloud database platform that's got a good balance of performance, flexibility and ease of use. Couchbase supports a variety of data access patterns, including key-value, JSON, SQL, text and vector search, as well as graph and time-series data. Its distributed architecture is geared for modern user-centric applications, and it can be integrated with leading public cloud providers, with enterprise-grade security and a developer portal with resources and tutorials.

Supabase is another good option, particularly if you're looking for an open-source alternative to Firebase. It offers a Postgres database, user authentication, real-time subscriptions and vector embeddings that can be used to integrate with machine learning models. Supabase supports frameworks like Next.js, Svelte and Flutter, and offers a free tier with unlimited API requests and 50,000 monthly active users, so it's a good option for many applications where you don't need to pay for every user.

If you're looking for a search and AI focused solution, Vespa is a unified search engine and vector database that supports vector search, lexical search and search in structured data. It's geared for building scalable search applications and combines fast vector search with machine-learned models, so it's a good option for AI-infused data sets and real-time analytics. Vespa also supports efficient machine-learned model inference and can be integrated with a variety of machine learning tools.