SingleStore

SingleStore is a MySQL wire-compatible SQL database that runs transactions, real-time analytics and vector search in one engine, managed or self-hosted.

SingleStore lets one database take the writes of a live application and the analytical queries on that same data, instead of splitting them across two systems. It is built by SingleStore, Inc., which began in 2011 as MemSQL and is based in San Francisco. Its Universal Storage table type pairs columnstore scan speed with rowstore seeks. The engine speaks ANSI SQL over the MySQL wire protocol and stores vectors, JSON and text beside relational tables. Helios is the managed cloud service, running on AWS, Azure and Google Cloud, and the same engine also installs as self-managed software. Inside the database, transactions lock individual rows, ALTER TABLE runs while the table stays readable and writable, and Row-Level Security limits which rows each user sees. Full-text search with BM25 ranking and native vector search share one SQL interface for hybrid queries. Continuous backups allow point-in-time restore, replica partitions take over automatically when a node fails, and Smart DR adds disaster recovery. Database Branching copies a database for testing, Code Engine loads Wasm functions, and Query History records past queries. Aura Intelligence sits on top: Analyst answers plain-English questions, and the Context Engine teaches agents how the data fits together. SingleStore suits SaaS teams that serve analytics to their own customers from live data. Ad tech platforms use it for bidding, targeting and fraud-prevention decisions made while an auction runs. Developers adding search, recommendations or AI agents get vector and keyword retrieval without a separate search engine. Platform teams that must keep data inside their own cloud account can run it there through Bring Your Own Cloud, or install it themselves. Most deployments start with getting data in. Pipelines read in parallel from Kafka, Amazon S3, HDFS and Apache Iceberg tables, and Flow copies snapshots and change data capture from MySQL or MongoDB without code. Embeddings become searchable the moment they are inserted, which serves recommendation and agent workflows. Engineers then work in SQL, one-click Python notebooks or auto-generated REST endpoints. Business users ask Analyst the same questions in plain English, against the same tables the application writes to.