Hard Cutover — Page 2

Validate pipeline changes with real data before production promotion.

Architectural choices, not headline pricing, determine what high-volume OLAP queries actually cost.

Isolated database branches let agents experiment safely against real production data.

Async inserts buffer bursty Kafka writes into properly sized parts.

Columnar storage eliminates wasted I/O, compression, and CPU inefficiency that rows cannot match.

Row and columnar storage create irreversible trade-offs that no amount of tuning can overcome.

WebAssembly's three primitives create provable isolation for untrusted code at database boundaries.

How columnar engines lose speed when calling foreign functions at row-oriented boundaries.

ADBC eliminates the serialization overhead that makes analytical queries slow on the client side.

Tail latency gets worse as data grows, not better, across most OLAP engines.

Business moments, not infrastructure speed, should set your analytics reliability targets.