Federated query latency problems cross system boundaries, which makes them hard to own internally — the Trino team blames the source, the source team blames Trino, and nobody has the full picture. AceMQ provides named senior engineers who can read both sides.
Latency regressions in Starburst are often environmental rather than structural: a source database changed an index, statistics went stale after a bulk load, a connector upgrade changed pushdown behavior, or coordinator queueing grew because concurrency crept up. Each of these looks identical from the BI tool — the dashboard is slow — and diagnosing them requires access and expertise on both sides of the connector.
Starburst Enterprise or Galaxy deployments on Kubernetes, VMs, or managed cloud, federating multiple production sources.
AceMQ engineers work from query event history, coordinator queue metrics, and source-side execution plans together, so a regression can be attributed correctly instead of argued about. Immediate mitigation may be a resource group change or a query rewrite; the follow-up addresses the statistics, connector configuration, or source-side index that caused it.
Latency regressions get attributed to the right system quickly, which shortens resolution and ends the cross-team standoff that usually accompanies federated query problems.
Stopping worker crashes caused by unbounded joins, missing spill configuration, and memory limits that do not match the concurrency the cluster actually sees.
Evaluating whether a federated query layer will actually work against a given set of source systems before the platform is committed to.
Whether you need architecture advisory, 24/7 support, or full managed services, AceMQ has the expertise to help.