Singlestore

SingleStore is a distributed SQL database that handles both OLTP transactional workloads and OLAP analytical queries in a single engine, eliminating the ETL complexity of maintaining separate transactional and analytical databases. Its MySQL-compatible SQL interface, native vector search capability, and managed cloud offering make it accessible for teams that want HTAP (hybrid transactional/analytical processing) without migrating off SQL. For agents needing both real-time transactions and complex analytics from the same data, SingleStore removes the operational overhead of maintaining separate databases.

Authentication uses username/password for MySQL protocol connections and API keys for the management API. The MySQL-compatible credential model means teams can use standard database credential management practices. Network isolation (VPC peering, IP allowlisting) is the primary security boundary for production SingleStore instances.

Documentation is comprehensive and covers the SQL dialect, vector search functions, and management API. The HTAP use case documentation — explaining how to structure tables and queries for combined workloads — is particularly useful for teams designing schemas that need to serve both operational and analytical queries efficiently.

The query interface is MySQL-compatible SQL — any MySQL client library works with SingleStore. The HTTP API endpoint enables SQL queries without a native client. SingleStore's vector search functions enable semantic similarity queries alongside transactional SQL without a separate vector database. The combination of transactional writes and sub-second analytical queries is the core value proposition for data-intensive agent applications.

Reliability is production-grade for the managed cloud offering, with the distributed architecture providing horizontal scaling and replication. SingleStore's separation of compute and storage enables independent scaling of analytical and transactional workloads. Teams running SingleStore for HTAP should monitor both transactional and analytical workload performance, as peak analytical query load can affect transactional latency.