At StarTree, we've taken a novel approach to querying Iceberg tables: applying Apache Pinot-style indexes to improve performance, lower costs, and increase concurrency… without moving data into a separate system.

In our tests on a ~1TB dataset, this reduced query latency significantly:

* 500+ QPS with sub-second latency * Complex aggregations <650ms * ~5–37x faster than ClickHouse and ~4–17x faster than Trino in the same setup

We welcome comments and input from this community!

This is really cool stuff. Amazing the efficiencies Pinot brings to data systems.

[Disclosure: I used to work at StarTree. Still a fan!]

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