How to Choose a Columnar Storage Format Based on Your Actual Workload

Selecting a columnar file format should begin with a clear analysis of the read path, including how many columns are queried, how often data changes, and how the system handles writer failures. Key variables such as projection, selectivity, concurrency, object-store latency, and update patterns must all be factored in before any benchmark result can be considered meaningful. The article warns that smaller files reduce wasted reads but increase object-store requests, while large row groups compress well but can force unnecessarily broad scans. Benchmarks should be run with the actual engines involved, covering both cold and warm scenarios, and must also test failure recovery, compaction, schema evolution, and rollback. The core advice is to choose the format that best fits your specific read, write, interoperability, and recovery requirements rather than the one with the most features.