One Copy, One Engine, No Seams

What this post added

This post critically analyzes the competitor's approach to unifying operational and analytical data, arguing that separate engines bolted onto shared storage create seams and introduce latency, especially for agentic workloads that require immediate consistency between writes and reads. It highlights SingleStore's 'Universal Storage' as a unified engine with a single data format (in-memory rowstore over columnstore) that provides immediate queryability for writes, handles updates and deletes efficiently, and supports multi-model data (relational, JSON, vectors) within a single engine. The post questions the competitor's 'LTAP' approach regarding its ability to handle updates and deletes with low latency and its readiness for write workloads.