## 2.28.0 (2026-06-16)

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

**Highlighted features in TimescaleDB v2.28.0**
* **Faster `first()` and `last()` queries on compressed data.**
TimescaleDB derives `first(value, time)` and `last(value, time)`
aggregates straight from the columnstore's batch metadata, skipping
batch decompression entirely. For the "latest reading per series"
lookups that time-series workloads run constantly, that means
meaningfully faster recency queries with no changes to your SQL queries.
* **Lighter, less disruptive continuous aggregate refreshes.**
`refresh_continuous_aggregate()` can now run incrementally in batches —
the same behavior refresh policies already use — enabling breaking large
manual refreshes into smaller chunks (tunable via `buckets_per_batch`,
`max_batches_per_execution`, and `refresh_newest_first`) instead of one
heavy operation. Refreshes also now take a lighter lock while processing
the invalidation log, so they no longer block unrelated concurrent
operations on the same continuous aggregate, improving behavior for
concurrent workloads.
* **Vectorized execution now covers `CASE` expressions.** TimescaleDB's
columnar executor can now evaluate `CASE ... WHEN` expressions directly
on compressed data, so queries using conditional logic stay on the fast
vectorized path instead of falling back to slower row-by-row
decompression. This speeds up a common pattern — conditional
aggregations and computed columns over compressed history — with no
query changes needed.
* **Add new aggregations to a continuous aggregate without rebuilding
it.** You can now run `ALTER MATERIALIZED VIEW <cagg> ADD COLUMN <name>
<type> GENERATED ALWAYS AS (<aggregate>) STORED` to add a new computed
aggregate to an existing continuous aggregate in place — no more
dropping and recreating the whole aggregate just to track one more
metric. New data populates the column going forward, letting your
rollups evolve alongside your application. (Existing rows start as
`NULL`; a forced refresh backfills them when you need historical
values.)

**Deprecation Notice: PostgreSQL 15 Support**
This release marks the final minor version of TimescaleDB that will
support PostgreSQL 15. Starting with our next release, version 2.29.0,
we will officially drop support for Postgres 15, and only support
Postgres 16, 17, and 18; however, all future patch releases within the
current 2.28 version cycle will continue to fully support it. We
recommend planning your PostgreSQL upgrades accordingly to ensure a
smooth transition.

**Deprecation Notice: `chunk_constraint` Catalog Table**
Please note that the `_timescaledb_catalog.chunk_constraint` table has
been dropped and temporarily replaced by a view, which introduces a
change to the underlying objects while maintaining current query
behavior. However, this compatibility view will be completely removed in
a future release. To ensure your queries remain compatible moving
forward, we strongly advise transitioning to the stable contracts
provided by our [informational
views](https://www.tigerdata.com/docs/reference/timescaledb/informational-views).

**Backward-Incompatible Changes**
* [#9934](#9934) Remove
adaptive chunking

**Features**
* [#4054](#4054) Support
`ANALYZE` and `VACUUM` on continuous aggregates by redirecting to the
underlying materialization hypertable
* [#9125](#9125) Increase
the parallelism of `SELECT` queries over compressed hypertables to
approximately match the uncompressed data size
* [#9410](#9410) Mark
`hypertable` and `chunk` as user catalog tables
* [#9416](#9416) Support
some forms of `CASE` expression in columnar aggregation and grouping
* [#9580](#9580) Add
`first` / `last` sparse indexes to compression
* [#9784](#9784) Use
`first` / `last` sparse index for `orderby` metadata on new compressed
chunks
* [#9668](#9668) Allow
database owner to configure hypertables and policies
* [#9701](#9701) Relax lock
during continuous aggregate invalidation log processing
* [#9730](#9730) Add
in-memory observability for compressed chunks
* [#9735](#9735) Improve
`GapFill` row count estimate
* [#9821](#9821) Allow
subquery results which are exec params as GapFill arguments
* [#9825](#9825) Support
`ADD COLUMN` on continuous aggregates
* [#9842](#9842) Suppress
continuous aggregate invalidation tracking during bulk loads
* [#9878](#9878) Remove
`chunk_constraint` catalog tracking for foreign keys
* [#9893](#9893) Remove
`chunk_constraint` catalog tracking for non-dimensional constraints
* [#9903](#9903)
Incremental refresh for `refresh_continuous_aggregate()`
* [#9915](#9915) Remove
`_timescaledb_catalog.chunk_constraint` table
* [#9938](#9938) Add
`rebuild_sparse_index` function
* [#9964](#9964) Add a
function to lock OSM chunk's dimension slice
* [#9980](#9980) Support
`first/last(value, time)` in `ColumnarIndexScan`

**Bugfixes**
* [#9708](#9708) Guard time
bucket parameter handling against bad input
* [#9745](#9745) Check
constraints when adding unique constraints to chunks
* [#9890](#9890) Fix
incremental refresh batch boundaries to align with variable-width
buckets and start only where a chunk and an invalidation overlap
* [#9914](#9914) Fix
use-after-free in segmentwise recompression
* [#9929](#9929) Fix
background jobs being bumped in the queue forever and never running
* [#9955](#9955) Fix wrong
results when using Batch Sorted Merge with no first-last index on a
non-leading order by column
* [#9967](#9967) Block
upgrade after downgrade with first/last indexes present
* [#9976](#9976) Fix wrong
results when comparing a date column to a `timestamptz` value
* [#9977](#9977) Fix `COPY
WHERE` into a hypertable with dropped columns
* [#9981](#9981) Fix
set-returning functions in the sort key of `ColumnarScan`
* [#9982](#9982) Reject
`ALTER TABLE ... INHERIT` when the parent is a hypertable
* [#9984](#9984) Fix
handling of `NOT VALID NOT NULL` constraint for query optimization
* [#9986](#9986) Handle
`MERGE WHEN NOT MATCHED BY SOURCE` on hypertables
* [#9988](#9988) Fix
`time_bucket_gapfill` function detection
* [#10003](#10003) Block
unsafe updates of unique columns on compressed chunks
* [#10024](#10024) Fix
`approximate_row_count` handling of Infinity
* [#10025](#10025) Fix
rename on compressed continuous aggregates
* [#10026](#10026) Fix
chunk skipping near `PG_INT64_MAX`


**New Settings**
* `skip_cagg_invalidation`: skip continuous aggregate invalidation
tracking for DML and DDL in the current session/transaction. Off by
default.
* `stats_max_chunks`: set the per-database compressed chunk statistics
cache capacity. Defaults to 1024 chunks; set to 0 to disable the
feature.

**Thanks**
* @Fabian-2596 for suggesting more accurate GapFill row count estimate
* @otjdiepluong for fixing spelling mistakes in timescaledb source code
comments
* @scimad and @Nosfistis for suggesting expanding coverage for gapfill
arguments

The last permutation released L1 (refreshing cagg_6h, in txn 3) and L2
(refreshing cagg_1d, in txn 1) from the same lock on the materialization
invalidation log simultaneously. Whether L2's scan of the hypertable
invalidation log saw the cagg_1d invalidation published by L1's final
commit was then pure scheduling: usually L2 read first and reported
"already up-to-date", but on loaded runners L1 could commit first,
making L2 refresh cagg_1d and diverge from the expected output.

Synchronize with a lock on cagg_6h's materialization hypertable instead.
An initial cagg_6h refresh of Jan 3 first publishes an invalidation so
L2 has real work. L1 then blocks on the lock mid-txn 3 -- after deleting
its processed log entries but before the commit that publishes the
downstream invalidations -- while L2 moves, cuts and collects its log
entries concurrently, blocking only when it starts materializing Jan 3
from cagg_6h. The outcome is deterministic: L2's invalidation processing
finishes while L1 is uncommitted, and its Jan 3 materialization reads
only buckets L1's Jan 1 refresh never touches. A regression of the
txn3-vs-txn2 non-blocking property (timescale#9701) would change the processed
invalidation set and fail the test.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>