Tomáš Vedral

Securing agent queries requires row filtering, column masking, and audit trails.

Shared OLAP caches need tenant isolation beyond query rate limits.

Agents investigate in parallel bursts that demand separate infrastructure from human analytics.

Columnar engines make denormalization practical when joins become the performance bottleneck.

Columnar storage changed join economics but did not eliminate the denormalization tradeoff.

Arrow database connections eliminate redundant row-column conversions, speeding up OLAP engines.

Columnar engines lose speed when UDFs break the system's core assumptions about data layout.

Deduplication only happens during merges, leaving duplicates queryable until that moment arrives.

Vendors withhold the test details buyers need to verify database performance claims themselves.

Averaging percentiles across hosts masks the true tail latency in your system.

Benchmarks only mean something when you know which eight variables stayed fixed.

Find the exact concurrency point where your database breaks before production does.