Welcome to the Party, Databricks
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SingleStore responds to Databricks' LTAP and Lakehouse//RT announcements, arguing that while Databricks has validated the market for unified transactional and analytical processing, their architecture still relies on two separate engines sharing a storage layer. SingleStore claims to have offered a single distributed SQL engine handling OLTP, OLAP, search, and application workloads since 2019. The post critiques Databricks' benchmarks as narrow (TPC-H Q6, single-table scans) and questions whether Postgres-compatible instances can handle the high-concurrency, horizontally-scalable demands of AI agents. The core argument: shared storage is not the same as a unified query engine, and routing logic between two systems creates operational complexity that doesn't disappear just because the storage layer is shared.
