SingleStore (formerly MemSQL) provides a unified database for transactions, analytics, and AI with native vector search capabilities. Free tier includes 3 workspaces with limited compute; Standard starts at $0.69/hour (S-00 instance). The database combines row-store (OLTP), column-store (OLAP), and vector indexes in single engine—avoiding ETL between systems for different workload types. Vector search achieves 98% accuracy at 100+ QPS on benchmarks with options for exact (EUCLIDEAN_DISTANCE) or approximate (ANN) search. JSON support enables document-style storage alongside relational data. Real-time ingestion through pipelines from Kafka, S3, and other sources. The notebook feature enables SQL + Python analysis similar to Jupyter. Full-text search adds keyword search alongside vector similarity. Best suited for applications requiring both transactional consistency and analytical speed without managing multiple databases. Page should cover: architecture explanation (row vs column store selection), vector search performance characteristics, pipeline ingestion setup, notebook capabilities, comparison with PostgreSQL + pgvector, pricing analysis for different workloads, and use cases for unified data platforms.