2025 Performance improvements¶

Important

Performance improvements often target specific query patterns or workloads. These improvements might or might not have a material impact on a specific workload.

The following performance improvements were introduced in 2025.

Released	Description	Impact
May 2025	Enhanced vectorized scanner availability for improved performance	Previously, the vectorized scanner could only be used with specific `ON_ERROR` settings (`ABORT_STATEMENT` or `SKIP_FILE`). This restriction has been removed. Now, you can enable the vectorized scanner with any `ON_ERROR` option, including `CONTINUE`, `SKIP_FILE_num`, and `'SKIP_FILE_num%'`. This change allows the performance-enhancing vectorized scanner to be used in more situations. You may see faster data processing as a result.
April 2025	Expands coverage of the Query Acceleration Service (QAS) to more queries.	Improves the heuristics that QAS uses to determine whether or not a query will benefit from acceleration. As a result, more queries are eligible for acceleration by QAS.
March 2025	Improves the batching of files during replication refresh operations.	Replication refresh jobs that replicate up to 8 GB of data will have less variance and more predictability.
March 2025	Improves performance for dynamic tables with incremental refresh mode using left outer joins.	Provides faster incremental refresh performance for dynamic tables that contain one or more left outer joins. Performance gains can be substantial depending on the workload.
March 2025	Adaptively optimizes compute and I/O resources for queries executed against Apache Iceberg™ tables.	Improves Apache Iceberg™ query performance and memory efficiency in high-concurrency scenarios.
February 2025	Tasks can be scheduled to run as frequently as every 10 seconds.	Reduces the time required between scheduled task executions.