Iceberg Query Performance Benchmark: StarTree vs. Trino vs. ClickHouse

This technical deep dive breaks down an Iceberg query performance benchmark comparing StarTree, Trino, and ClickHouse on a 12.2B-row Iceberg dataset. For data platform teams, Iceberg provides an open and flexible table format. But at scale, query performance depends on more than whether an engine can read the data. Latency, caching behavior, CPU usage, data reads, and cost per query all determine whether the architecture can support interactive workloads efficiently. In this session, we walk through the benchmark setup, query patterns, results, and engineering details behind the numbers. You’ll see how each engine handled the same dataset and workloads, where performance diverged, and how query architecture affected infrastructure efficiency. Topics covered: Benchmark methodology across StarTree, Trino, and ClickHouse Query latency results across common Iceberg workloads Caching behavior and where it changed performance CPU usage, data reads, and cost-per-query analysis How indexing changes query execution over Iceberg tables What platform teams should consider when designing for sub-second performance and predictable infrastructure cost Watch the full session to understand how different query architectures perform on Iceberg at scale — and what the results mean for teams evaluating open lake data infrastructure. Read the full benchmark: https://stree.ai/49XuEno LEARN MORE ► Learn about StarTree and Apache Pinot™: https://docs.startree.ai/ CONNECT Subscribe on YouTube: https://stree.ai/sub Community Slack: https://stree.ai/join-slack Twitter: https://twitter.com/startreedata Linkedin: https://www.linkedin.com/company/startreedata GitHub: https://github.com/startreedata Site: https://startree.ai ABOUT STARTREE StarTree, powered by Apache Pinot™, is the platform for continuous insights at scale. StarTree turns raw data streams—like clickstreams, logs, vector embeddings, and sensor data—into real-time analytics. It powers customer-facing data products, agent-facing data products, and operational intelligence. Apache Pinot™ delivers real-time analytics by design, rather than extension—built from the ground up to ingest massive data streams with millisecond freshness, execute sub-second aggregations, and support tens of thousands of queries per second. Pinot achieves this while radically reducing infrastructure costs by scanning less data and extreme compression. StarTree was founded by the core software engineering team and inventors of Apache Pinot™, which currently powers hundreds of user-facing applications at companies across industries, including Uber, LinkedIn, Stripe, Target, 7Eleven, NuBank, Etsy, Walmart, Together AI, and more. #apachepinot #realtimeanalytics #startree #apacheiceberg #trino #clickhouse