Starburst's value depends on connectors doing work at the source. When pushdown silently fails, Trino compensates by streaming entire tables across the network and filtering them in worker memory, which is the slowest possible way to answer the query. AceMQ finds where pushdown is breaking and fixes the conditions that break it.
Pushdown failures are quiet. A query that should send a filtered, aggregated request to Snowflake or PostgreSQL instead issues a full table scan because a CAST on the predicate column defeated the connector's rewrite, or a function has no source equivalent, or the join key types differ across catalogs. Teams see slow queries and add workers, which increases cost without touching the actual problem.
Starburst Enterprise or Galaxy federating relational sources, object storage, and warehouse connectors across on-premises and cloud.
AceMQ reads EXPLAIN and EXPLAIN ANALYZE output for the slowest recurring queries to see exactly which operators the connector accepted and which stayed in Trino. Each blocked pushdown is traced to its cause — type mismatch, unsupported function, missing statistics — and fixed at the query, view, or connector configuration level. Cost-based optimization is then given the statistics it needs to pick sane join orders.
Queries that previously scanned entire remote tables return to source-side execution, and cross-network data volume drops sharply. Customers generally find they can defer adding Trino workers because the cluster is no longer doing work the source database should have done.
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.