Query Performance Optimization in Open Table Formats

A layered analysis of query performance across Apache Iceberg, comparable Delta Lake concepts, and query engine innovations.

• Reduce unnecessary I/O before it becomes unnecessary spend: See how pruning, fetch reduction, and serving-layer efficiency cut wasted reads across open table architectures.
• Lower latency by eliminating work across layers: Understand how performance improves when less data is scanned, fewer remote reads are required, and execution is better aligned to the workload.
• Reduce operational overhead as workloads scale: Learn why performance no longer comes from a single optimizer and what platform teams must manage across metadata, file access, and serving.
• Make high-concurrency workloads more practical on open table formats: Explore the architectural patterns that help platform teams support high QPS, low-latency queries without linear cost growth.

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