When HTAP Wins: Migrating an AI Forecasting Platform to SingleStore
Migrating an AI-driven supply-chain forecasting platform from MariaDB onto SingleStore, where a single HTAP engine handling both transactional and analytical workloads fit the shape of ML-driven operations better than separate systems.
For an AI-driven forecasting workload — operational reads, analytical queries against historical patterns, model outputs feeding back into operational systems — the conventional OLTP-plus-warehouse split introduces exactly the latency the product cannot afford. This migration consolidated onto SingleStore’s hybrid transactional/analytical engine instead.
The full write-up will cover:
- The workload shapes where single-engine HTAP genuinely wins, and where it does not
- Migration mechanics from MariaDB: schema, data movement, query-pattern conversion
- Column-store internals serving low-latency analytics against operational data
- How this experience maps onto the current HTAP-versus-lakehouse architectural debate
Full case study coming soon.