TimescaleDB 2.26: 3.5x Faster time_bucket() Aggregations, 70x Faster Summary Queries, and Faster Multi-Column Lookups

TimescaleDB 2.26 introduces significant performance enhancements, aiming to improve the efficiency and speed of analytical queries on Postgres. This release extends the vectorized columnstore engine to support more query patterns, resulting in up to 3.5x faster time_bucket() aggregations and up to 70x faster summary queries using ColumnarIndexScan, which allows summary queries to be answered directly from chunk-level sparse index metadata. Additionally, new composite bloom filters improve multi-column lookups by enabling the query engine to skip unnecessary data before decompression, resulting in over 2x faster performance for SELECT and UPSERT workloads. The update also includes faster text aggregates, improved background worker reliability, and better replication and stability, with these enhancements generally taking effect without requiring changes to existing queries.

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