timescale/timescaledb 2.26.0

2.26.0 (2026-03-24)

on GitHub

This release contains performance improvements and bug fixes since the 2.25.2 release. We recommend that you upgrade at the next available opportunity.

Highlighted features in TimescaleDB v2.26.0

• The vectorized aggregation engine now evaluates PostgreSQL functions directly on columnar arguments and stores the results in a columnar format to preserve the high-speed execution pipeline. For analytical queries that leverage functions like time_bucket() in grouping or aggregation expressions, the function is evaluated natively without falling back to standard row-based processing. This enhancement ensures that the remainder of the query can seamlessly continue using the highly efficient columnar pipeline, yielding performance improvements of 3.5 times faster.
• The query execution engine now supports composite bloom filters for SELECT and UPSERT operations, pushing down multi-column predicates directly to compressed table scans. This optimization bypasses costly batch decompression by automatically selecting the most restrictive bloom filter to quickly verify if target values are present. Showing over two times faster query performance when a composite bloom filter is used. Additionally, query profiling now includes detailed EXPLAIN statistics to monitor batch pruning and false-positive rates.
• The custom node ColumnarIndexScan adjusts the query plan to fetch values from the sparse minmax indexes, improving query performance on the columnstore by up to 70x. For analytical queries that leverage functions like COUNT, MIN, MAX, FIRST (limited), and LAST (limited), the sparse index is being read instead of decompressing the batch.

Features

• #9104 Support min(text), max(text) for C collation in columnar aggregation pipeline
• #9117 Support functions like time_bucket in the columnar aggregation and grouping pipeline.
• #9142 Remove column dropped from _timescaledb_catalog.chunk
• #9238 Support non-partial aggregates with vectorized aggregation
• #9253 Support VectorAgg in subqueries and CTEs
• #9266 Add support for HAVING to vectorized aggregation
• #9267 Enable ColumnarIndexScan custom scan
• #9312 Remove advisory locks from bgw jobs and add graceful cancellation
• #8983 Add GUC for default chunk time interval
• #9334 Fix out-of-range timestamp error in WHERE clauses
• #9368 Enable runtime chunk exclusion on inner side of nested loop join
• #9372 Push down composite bloom filter checks to SELECT execution
• #9374 Use bloom filters to eliminate decompression of unrelated compressed batches during UPSERT statements
• #9382 Fix chunk creation failure after replica identity invalidation
• #9398 Fix chunk exclusion for IN/ANY on open (time) dimensions

Bugfixes

• #9401 Fix forced refresh not consuming invalidations
• #7629 Forbid non-constant timezone parameter in time_bucket_gapfill
• #9344 Wrong result or crash on cross-type comparison of partitioning column
• #9356 Potential crash when using a hypertable with partial compression or space partitioning in a nested loop join
• #9376 Allow CREATE EXTENSION after drop in the same session
• #9378 Fix foreign key constraint failure when inserting into hypertable with referencing a foreign key
• #9381 Data loss with direct compress with client-ordered data in an INSERT SELECT from a compressed hypertable
• #9413 Fix incorrect decompress markers on full batch delete
• #9414 Fix NULL compression handling in estimate_uncompressed_size
• #9417 Fix segfault in bloom1_contains

GUCs

• default_chunk_time_interval: Default chunk time interval for new hypertables. This is an expert configuration, please do not alter unless recommended from Tiger Data.
• enable_composite_bloom_indexes: Enable creation of bloom composite indexes on compressed chunks. Default: true

Thanks

• @bronzinni for reporting an issue with foreign keys on hypertables
• @janpio for reporting an issue with CREATE EXTENSION after dropping and recreating schema
• @leppaott for reporting a deadlock when deleting jobs