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Kanishga Subramani
Kanishga Subramani

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ClickHouse® 26.8 LTS Release: What's New and Why It Matters

#clickhouse #devops #analytics #database

ClickHouse® 26.8 is the newest LTS release, and it is a substantial one: 21 backward-incompatible changes, 49 new features, 127 performance improvements, and around 30 settings that changed their default value.

This article covers 26.8 on its own — what landed, what breaks, and what to verify before you upgrade.

Release status at time of writing (27 August 2026). ClickHouse® 26.8 has been announced, but the release is not fully published yet and the upstream changelog still marks the 26.8 section as in progress. Confirm the current release status before you plan an upgrade window.

In This Article

  • At a glance

  • Breaking changes

    • Ingestion and the write path
    • Type and function semantics
    • Query planning and output
    • Security and configuration
    • Removals
    • Monitoring and introspection

  • Default settings that changed in 26.8

    • Behaviour
    • Security
    • Performance (enabled by default)
    • MergeTree - on-disk formats

  • What's new

    • SQL surface
    • Server and operations
    • Observability
    • Joins and text search
    • Data lakes
    • AI functions

  • Performance

  • Upgrade checklist

  • Summary

At a Glance

Category Entries
Backward incompatible changes 21
New features 49
Experimental features 48
Performance improvements 127
Improvements 138
Bug fixes 556

Breaking Changes

All 21 breaking changes, grouped by what they affect.

Ingestion and the Write Path

max_insert_threads now defaults to auto

It resolves to the number of CPU cores available to the server, parallelising INSERT SELECT by default. It can also parallelise the writing side of a plain INSERT where the destination write path can safely fan out.

Two consequences worth planning for: the number of parts created by such queries changes, and so does the order of inserted rows.

If you have tight parts_to_throw_insert thresholds, or anything depending on insertion order — a non-deterministic ORDER BY tie-break, _part or _block_number assumptions, a ReplacingMergeTree without a proper version column — test this before rolling out.

A detail that catches people diffing configurations: the declared default is 0 in both 26.7 and 26.8.

What changed is the setting's type, from UInt64 to MaxThreads.

Under UInt64, both 0 and 1 meant single-threaded; under MaxThreads, 0 resolves to auto.

So the value column in system.settings reads 0 before and after, while the behaviour has flipped.

Upstream's own compatibility mapping records the change as 1 → 0 for this reason — 1 is what you now set to get the old behaviour, not what the declaration used to say.

Restore with:

SET max_insert_threads = 1;
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Or use a compatibility version below 26.8.

Lightweight UPDATE patch parts use a new v2 on-disk format

They are now sorted by:

(sorting_key..., _block_number, _block_offset)
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and applied with a new merging algorithm.

Peak memory during apply is bounded by the largest equal-sort-key run rather than the full patch, and updates crossing merge boundaries no longer fall back to an in-memory Join apply.

Old-format patch parts remain readable.

For replicated clusters this requires a rolling-upgrade pin.

Note that patch_parts_version is a MergeTree setting rather than a session setting:

<merge_tree>
    <patch_parts_version>v1</patch_parts_version>
</merge_tree>
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Or:

ALTER TABLE my_table MODIFY SETTING patch_parts_version = 'v1';
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Hold that until every replica is on 26.8, then remove it.

Object-storage disk transactions

Object-storage disk transactions now use the metadata storage's native transactions by default instead of the previous fake transactions.

The upstream changelog does not explain why this is listed as backward-incompatible, so treat it as worth testing if you run object-storage disks.

disable_insertion_and_mutation changes

disable_insertion_and_mutation now also stops background consumption from Kafka, RabbitMQ and NATS tables, while still permitting direct writes to external storage.

Gated Kafka2, NATS and RabbitMQ tables no longer initialise consumers for a direct SELECT.

Separately, message_queue_disable_insertion now requires a server restart to take effect.

Type and Function Semantics

Unquoted JSON numbers are now Unix timestamps

In JSONEachRow and similar formats, an unquoted number for a DateTime or DateTime64 column is read as a Unix timestamp with optional sub-second precision, consistent with Values, CAST and toDateTime64.

Previously a fractional value such as:

1703363853.035
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was rejected outright, and a bare integer such as:

1703363853
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was read as the raw scaled value of DateTime64, producing a 1970 timestamp.

Quoted strings and ClickHouse®'s own JSON output are unaffected.

For most pipelines this is a silent fix.

If yours was compensating for the old raw-value behaviour, it will now double-correct.

Restore with:

SET input_format_read_datetime_number_as_raw_value = 1;
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Date32 range extended

The Date32 range is extended from:

[1900-01-01, 2299-12-31]
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to:

[0000-01-01, 9999-12-31]
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matching DateTime64.

Parsing and conversions accept the extended range instead of silently clamping.

The compatibility note matters: in toDate32(N), values in:

[120530, 2932896]
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are now interpreted as day numbers — dates from 2300-01-01 to 9999-12-31 — rather than Unix timestamps in early 1970.

Numbers below the day number of 0000-01-01, and timestamps after 9999-12-31, saturate to the new boundaries.

arrayIntersect and arraySymmetricDifference deduplication fixed

A value repeated inside a single argument is no longer treated as though it appeared in several arguments.

A value now counts for an argument only when it was present in every argument before it, so the result contains exactly the values present in all arguments.

Examples:

SELECT arrayIntersect([1], [2], [1, 1]);
-- []

SELECT arrayIntersect([1, 2], [2], [1, 1, 2]);
-- [2]

SELECT arraySymmetricDifference([1], [2], [1, 1]);
-- [2, 1]

SELECT arraySymmetricDifference([1], [2, 2]);
-- [2, 1]
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arrayUnion is unaffected.

As part of the same change, arrayIntersect builds its hash table from the smallest argument rather than all of them — up to 1.85x faster and a third less memory when argument sizes differ significantly.

Window functions over AggregateFunction columns are rejected

A window PARTITION BY or ORDER BY over an AggregateFunction column now raises ILLEGAL_COLUMN, as top-level ORDER BY over such a column already did.

Previously at least one analyzer accepted it, and window PARTITION BY partitioned differently depending on max_threads.

The refusal covers states nested in Array, Tuple, Map, Variant or SimpleAggregateFunction.

A SimpleAggregateFunction over an ordinary type, QBit, and GROUP BY or DISTINCT over a state are all unaffected.

Timespan settings that overflow Int64 microseconds are rejected

This applies to millisecond and second settings.

Query Planning and Output

Trivial views over Distributed tables are pushed to the shards

For a view whose body is a plain SELECT over a single Distributed table, the whole outer query now goes to the shards.

This is the new:

optimize_trivial_view_pushdown_to_distributed
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setting, enabled by default.

Observable behaviour changes in two ways:

  • FINAL and SAMPLE written on the view reference are now propagated to the shard-local table instead of being ignored.
  • extremes is not reported on single-shard clusters.

If you had views where FINAL was silently a no-op, results will change.

Set the setting to 0 to restore the previous behaviour:

SET optimize_trivial_view_pushdown_to_distributed = 0;
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EXPLAIN SYNTAX returns a single record

The reformatted query comes back as one String value with embedded newlines rather than one record per line.

So:

SELECT count() FROM (EXPLAIN SYNTAX ...);
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returns:

1
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To restore the old behaviour:

SET explain_syntax_single_record = 0;
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Other EXPLAIN kinds — PLAN, PIPELINE, AST — keep their per-line tree output.

Security and Configuration

A clear theme this release: the server no longer opens filesystem paths supplied from SQL, because it opens them with its own privileges.

MySQL source TLS credentials

MySQL source TLS credentials:

  • ssl_ca
  • ssl_cert
  • ssl_key

can no longer be given as file paths from SQL — not in CREATE NAMED COLLECTION, query arguments, or CREATE DICTIONARY.

Paths remain supported in the server configuration file.

Elsewhere, pass the contents via the new:

  • ssl_ca_pem
  • ssl_cert_pem
  • ssl_key_pem

parameters, which are masked in logs and SHOW output the way passwords are.

NATS credentials move inline

The new nats_credentials setting takes the same payload as a .creds file.

nats_credential_file is no longer accepted from SQL.

It can only be set in:

  • a named collection defined in the server configuration, or
  • nats.credential_file in the server configuration itself.

A query may replace a configured path with inline nats_credentials unless the operator pinned it with:

<nats_credential_file overridable="false">
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Tables created before the restriction keep working.

PostgreSQL database engines respect remote_url_allow_hosts

The PostgreSQL and MaterializedPostgreSQL database engines now honour remote_url_allow_hosts, as the table engine, table function and DDL-created dictionaries already did.

With it configured, CREATE DATABASE and user-issued ATTACH DATABASE pointing at disallowed hosts fail with:

UNACCEPTABLE_URL
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Existing databases still load at startup.

SYSTEM ... CACHE ON CLUSTER privilege checks are granular

Each command now uses its own privilege rather than the SYSTEM DROP CACHE group.

This lets a holder of a single granular cache privilege run its matching command, and prevents a holder of the group from running:

SYSTEM SYNC FILESYSTEM CACHE ON CLUSTER
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without:

SYSTEM SYNC FILESYSTEM CACHE
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include_from no longer defaults to /etc/metrika.xml

That file was previously used for configuration substitutions whenever it existed, even with nothing in the ClickHouse® configuration referring to it.

If you relied on it, add the element explicitly:

<include_from>/etc/metrika.xml</include_from>
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Separately loaded users.xml and XML dictionary configs each need their own include_from element.

Removals

The library dictionary source is gone 

SOURCE(LIBRARY(...))
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now fails with:

UNKNOWN_ELEMENT_IN_CONFIG
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The dictionaries_lib_path server setting is obsolete with no effect.

Apache Arrow library-based reader and writer removed

The Apache Arrow library-based reader and writer for Arrow and ArrowStream are removed.

The native ClickHouse® implementation, default since 26.7, is now the only one.

The following settings are still accepted but have no effect:

input_format_arrow_use_native_reader
output_format_arrow_use_native_writer
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So a query that set them to 0 to force the Apache Arrow path now silently uses the native one.

Experimental ALP(STD) codec changes

The experimental ALP(STD) codec now performs Float32 scaling arithmetic in Float64.

This improves compression ratios and eliminates exception-heavy compression of decimal data, but Float32 values written by earlier versions may decode 1 ULP differently.

Monitoring and Introspection

Asynchronous metrics can now be Map-typed

Asynchronous metrics can now be Map-typed, and the per-CPU-core and per-device metrics were consolidated.

For example:

OSUserTimeCPU0
OSUserTimeCPU1
...
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became a single:

OSUserTimeCPU
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metric holding a map from core number to value.

The same applies to the other:

  • OS*TimeCPU*
  • CPUFrequencyMHz_*
  • Temperature*
  • EDAC*
  • Block*_*
  • Network(Receive|Send)*_*
  • Disk*_*
  • *BlobsQueueEstimate
  • AsyncLogging*QueueSize

metrics.

Downstream effects:

  • system.asynchronous_metrics gains key_values Map(LowCardinality(String), Float64).
  • The value column is NaN for these metrics.
  • system.asynchronous_metric_log logs one row per key via a new key column.
  • The Prometheus endpoint exports them with a label, for example: 
ClickHouse®AsyncMetrics_BlockReadBytes{device="sda"}
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  • Graphite's MetricsTransmitter sends them as: 
<prefix>.<Metric>.<key>
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This is the change most likely to break existing dashboards.

Panels keyed on the old metric names will not error — they will simply return nothing, which is easy to miss.

system.users.valid_until changed type

system.users.valid_until changed type from:

Array(DateTime)
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to:

Array(DateTime64(0))
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so deadlines beyond the year 2106 are represented exactly.

Tooling reading this column needs to handle the new type.

This arrived alongside a new:

VALID FOR <interval>
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clause on CREATE USER and ALTER USER.

It is a shorthand for VALID UNTIL, where the deadline is computed at query execution time and stored in VALID UNTIL form.

Default Settings That Changed in 26.8

Around 30 core settings and several MergeTree settings changed their defaults.

These do not appear in the breaking-change list but will change behaviour on upgrade.

Behaviour

Setting Previous New
max_insert_threads 1 - single-threaded auto - all available cores
input_format_read_datetime_number_as_raw_value true false
optimize_trivial_view_pushdown_to_distributed - true
explain_syntax_single_record false true
filesystem_cache_wait_for_concurrent_download_timeout_milliseconds 60000 1000

Security

Setting Previous New
ai_function_allow_insecure_endpoint true false
ai_function_max_api_calls_per_query 0 (unbounded) 1000

Performance (Enabled by Default)

The following performance improvements are now enabled by default:

  • enable_adaptive_aggregator
  • enable_group_by_top_k_optimization
  • enable_packed_string_keys_in_aggregation
  • enable_parallel_single_level_merge
  • read_in_order_use_virtual_row
  • query_plan_push_down_volume_reducing_functions
  • query_plan_short_circuit_constant_false_join
  • use_query_condition_cache_for_top_k
  • allow_distinct_partitions_independently
  • allow_window_partitions_independently
  • allow_creating_set_partitions_independently
  • optimize_trivial_count_with_sparsity_filter
  • input_format_parquet_spatial_filter_push_down
  • query_plan_optimize_count_from_text_index
  • materialize_statistics_on_insert

The last setting has a 25 GiB table-size cap.

MergeTree - On-Disk Formats

Setting Previous New Compatibility
text_index_serialization_version v1_with_codec v2_with_positions Older servers cannot read the new format. Pin to v1 during a rolling upgrade
packed_skip_index_max_bytes 0 1 MiB New parts only; still readable by older servers, though pre-26.6 ignores packed indices for pruning
compute_exact_num_defaults_for_sparse_columns false true The flag in serialization.json is ignored by older versions, so parts survive downgrade
text_index_posting_list_apply_mode materialize lazy Posting lists decoded on demand
text_index_max_memory_usage_before_flush unlimited 1 GiB Memory-based flush trigger for index builders

One protocol-level note: the native protocol changed how String columns are transmitted — a separate stream of cumulative byte offsets followed by concatenated data — once both peers are on revision 54489 or later.

This is around 4x faster for client-side reads.

It is negotiated by protocol revision, so old clients and servers are unaffected, but maintainers of custom native-protocol clients should handle the new revision.

What's New

SQL Surface

Pipe operators

GoogleSQL-style |> chaining is now supported.

Each pipe wraps the preceding query in a subquery, so the resulting AST matches the nested equivalent.

Example:

FROM events
|> WHERE status = 'active'
|> AGGREGATE count() AS total GROUP BY user_id
|> ORDER BY total DESC
|> LIMIT 10;
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In a query starting with FROM, SELECT is now optional and defaults to:

SELECT *
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GROUPS window frame mode

GROUPS is a SQL:2011 window frame mode.

Frame boundaries count whole peer groups rather than physical rows or value distances, completing the set alongside ROWS and RANGE.

Query AST as JSON

New functions:

parseQueryToJSON
formatQueryFromJSON
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An experimental ClickHouse®_json dialect is also available behind:

enable_json_ast_dialect
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Also new:

  • arr[indexes] for subscripting an array with an array of positions
  • notHas
  • gini
  • mergedJSONPatch

Server and Operations

SQL-defined HTTP handlers

CREATE HANDLER, ALTER HANDLER and DROP HANDLER define custom HTTP endpoints from SQL.

Handlers can be persisted locally or in Keeper.

Supporting additions include:

  • currentHandler()
  • currentRequestURL()
  • system.handlers
  • http_handler_name in system.query_log
  • http_request_url in system.query_log

For teams maintaining small API services that exist only to expose a query over HTTP, this is worth evaluating.

run_query_in_background

The server accepts the query, returns immediately, and runs it to completion regardless of what happens to the connection.

Track it by query_id in:

  • system.processes
  • system.query_log

This is aimed at long-running operations such as:

  • INSERT SELECT
  • CREATE TABLE AS SELECT
  • POPULATE

Atomic POPULATE

A plain:

CREATE MATERIALIZED VIEW ... POPULATE
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is now locally atomic, controlled by:

materialized_views_populate_atomically
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and enabled by default.

Rows inserted through the same server during population are no longer missed or duplicated.

This applies to the local insert path only and requires a snapshot-capable source — the MergeTree family or Memory.

CREATE OR REPLACE, REPLACE, and Replicated databases keep the legacy path.

POPULATE also works with TO now.

Introspection port

A native-protocol TCP listener starts before tables attach and stops after detach completes.

This makes:

SHOW PROCESSLIST
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and:

system.stack_trace
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available during startup and shutdown.

Alongside it, shutdown_wait_unfinished moved from 5 seconds to 120 seconds.

The old default was shorter than the connection poll interval.

Keeper on-disk storage

Keeper now supports on-disk storage via a custom LSM tree.

Enable with:

use_lsmt_storage = true
storage_memory_only = false
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Configure through:

data_storage_path
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or:

data_storage_disk
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This can point at an s3_plain disk for S3.

The Keeper dashboard also gains a Cluster tab showing Raft membership as a topology graph.

HTTP URL-path access to tables

Tables can now be accessed through HTTP URL paths such as:

/database/table.format.gz?filter=a>0
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This is behind a set of http_allow_* opt-ins.

Framing output formats

framing_output_format multiplexes:

  • data chunks
  • totals and extremes
  • progress
  • profile events
  • logs
  • exceptions

into a single HTTP stream.

Available formats include:

EventStream
JSONEachPacketBase64
JSONEachPacketString
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Also new:

  • default_session_user as a server setting
  • Prometheus constant labels via a <labels> element inside <prometheus>
  • ALTER TABLE ... MODIFY PROJECTION to change projection settings without a rebuild

Projection changes are applied lazily via merges.

Observability

Several useful observability improvements landed in 26.8:

system.user_query_log

Every user sees their own query log rows without needing access to:

system.query_log
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create_union_system_log_tables

This creates auto-maintained all_... tables such as:

system.all_query_log
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These union:

  • a log table
  • its rotated versions
  • the same table across cluster replicas

remote, remoteSecure, cluster and clusterAllReplicas now accept a trailing SETTINGS clause.

system.mutations.finish_time

Provides mutation duration without having to infer it.

system.tables.skipping_indices_types

Provides a cheap summary of which index types a table uses.

Play UI

The Play UI now supports:

  • server-side sorting
  • filtering
  • paging

These settings are encoded in the page URL so a shared link reproduces the result.

Joins and Text Search

IEJoin

IEJoin is a sort-based algorithm for ON clauses containing two inequality comparisons.

Previously such joins ran as a CROSS JOIN with a filter, and only as INNER.

Enable by adding:

ie_join
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to:

join_algorithm
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parallel_full_sorting_merge

parallel_full_sorting_merge shards a full sorting merge join by join-key hash across threads.

Upstream benchmarks put it around:

  • 2.4x faster
  • 3.3x lighter on memory

than parallel_hash, while keeping streaming memory behaviour.

The result is unordered.

New text index tokenizers

New tokenizers include:

  • japanese — MeCab
  • chinese — jieba-style dictionary plus HMM
  • icu — locale-aware Unicode segmentation
  • splitByRegexp — keeps tokens such as C++ and C# intact

Data Lakes

A number of data-lake integrations have been expanded.

BigQuery

A bigquery table function and BigQuery table engine are now available.

Authentication supports:

  • OAuth token
  • service account JSON
  • refresh token

Snowflake Horizon

Snowflake Horizon catalog support is available for reading and writing Iceberg.

S3 Tables

The S3 Tables catalog now supports:

INSERT
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Puffin

Puffin file format support has been added.

URL database engine

A URL database engine and s3_base setting complete the URL unification.

ClickHouse®-local's default database now uses it with a file:// base.

This means:

SELECT * FROM 'https://example.com/data.csv'
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works directly.

AI Functions

The experimental:

  • aiSimilarity
  • aiFilter
  • aiRedact

functions were hardened in this release.

Insecure http endpoints to remote hosts are denied by default.

Outbound calls per query are bounded at:

1000
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Provider error responses are also sanitised before logging.

Performance

ClickHouse® 26.8 contains 127 performance entries, with the majority enabled by default.

The improvements with the broadest reach include:

Aggregation

A new adaptive parallel GROUP BY allows each thread to aggregate into its own cache-resident hash table until it hits a threshold, then freezes it.

Other aggregation improvements include:

  • bounded-heap pruning for GROUP BY ... ORDER BY ... LIMIT
  • smaller hash-table cells for single-String keys
  • parallelised final merge of single-level tables
  • aggregations without aggregate functions now use HashSet rather than HashMap

The latter can be up to 1.8x faster.

Reads

Lazy materialization for Parquet on object storage can significantly reduce I/O.

For example, on a 200 MB S3 file:

ORDER BY ... LIMIT 10
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read:

3.3 MB
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instead of:

171 MB
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That represents:

  • 51x less I/O
  • 8x faster

read_in_order_use_virtual_row is enabled by default and reduces peak memory when reading in primary key order across many parts.

The Parquet V3 reader also gains dictionary-page-based row group skipping.

Per-Partition Processing

DISTINCT, window functions and IN (subquery) set building can now keep each partition's rows in a single stream when the partition expression is a deterministic function of the relevant columns.

This skips the hash scatter entirely.

The Important Trade-Off

The trade-off worth stating plainly:

Query plans and resource usage will change after upgrading, even for queries you did not touch.

Most workloads benefit, but plan for a period of observation rather than assuming parity.

Upgrade Checklist

Before Upgrading

Check for dictionaries using the removed library source:

SELECT name, source
FROM system.dictionaries
WHERE source ILIKE '%library%';
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Check non-default settings you are carrying:

SELECT name, value, default
FROM system.settings
WHERE changed;
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And:

SELECT name, value
FROM system.server_settings
WHERE changed;
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Then check by hand:

  • Named collections and dictionaries using MySQL ssl_ca / ssl_cert / ssl_key paths
  • NATS tables or collections using nats_credential_file
  • Reliance on the implicit /etc/metrika.xml substitutions file
  • PostgreSQL / MaterializedPostgreSQL databases against hosts outside remote_url_allow_hosts
  • Ingestion clients writing unquoted epoch numbers into DateTime64 columns via JSONEachRow
  • Queries using toDate32 on epoch-second values
  • Anything parsing EXPLAIN SYNTAX output
  • Tooling reading system.users.valid_until
  • Dashboards keyed on individual per-CPU or per-device asynchronous metric names

During a Rolling Upgrade

Pin:

patch_parts_version = 'v1'
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and:

text_index_serialization_version = 'v1_with_codec'
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until every replica is on 26.8.

Then remove both pins.

After Upgrading

Watch part counts and merge queue depth in:

system.parts
system.merges
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for the max_insert_threads effect.

Also monitor:

system.errors
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for:

UNACCEPTABLE_URL
ILLEGAL_COLUMN
UNKNOWN_ELEMENT_IN_CONFIG
BAD_ARGUMENTS
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These cover most of the new rejections.

If you want to stage the transition:

SET compatibility = '26.7';
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This restores the majority of the default flips in one move, letting you upgrade the binaries first and enable the new behaviour deliberately afterwards.

It does not cover removals or type changes — those need code fixes, which the checks above should surface.

Summary

The three changes most likely to affect a running deployment are:

1. max_insert_threads defaulting to auto

This changes part creation patterns and insert row order on every:

INSERT SELECT
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2. Asynchronous metric consolidation

This can break dashboards silently rather than loudly.

3. Patch parts v2 format

This requires a rolling-upgrade pin on replicated clusters.

Beyond that, 26.8 is a strong release.

The security tightening around credential handling is overdue and welcome.

The operational additions — SQL-defined handlers, background queries, atomic POPULATE, and the introspection port — address real gaps.

And the 127 performance improvements, mostly enabled by default, represent a meaningful return on the upgrade work.

The key lesson is simple:

Treat ClickHouse® 26.8 as a real upgrade project, not just a version bump.

Review the defaults, test workload behaviour, validate observability, and plan the rollout carefully.

Read more... https://www.ch-ops.io/blog/clickhouse-268-lts-release-whats-new-and-why-it-matters

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