If you want a fully managed DBaaS with AI-powered code help and high-performance transactional performance, Couchbase is a top contender. It's a NoSQL cloud database platform for business-critical applications that combines a high-performance memory-first architecture with AI-assisted coding. Couchbase supports a variety of data access patterns, including key-value, JSON, SQL, text and vector search, and has features like distributed database architecture and cloud deployment on users' terms.
Another contender is SingleStore, a real-time data platform that's good for petabyte-scale data. SingleStore is designed for intelligent applications and can house both transactional and analytical data in a single engine. It can ingest streaming data at high throughput, respond to queries in milliseconds, and support multiple data models, including JSON and time-series data. The platform also has elastic scaling and high availability features, so it can handle demanding workloads.
If you're already using the Postgres database engine, EDB Postgres AI is a unified platform for transactional, analytical and AI workloads. It's got native AI vector processing, an analytics lakehouse and high availability up to 99.999% uptime. The platform has hybrid data management and migration tools from legacy systems like Oracle. That makes it a good option for bringing AI and analytics into Postgres-based workloads.
Last, Databricks is a broad data intelligence platform that uses generative AI to help you manage data, run analytics and govern it all. It's built on a lakehouse architecture, and Databricks supports a wide range of tools and integrations, so you can build, deploy and run AI applications right on your data. It's designed for democratized insights and low-cost operations, and offers a free trial for new users to try it out.