Manticore Search 27.1.5 has been released. This release brings built-in authentication and authorization, sharded tables, conversational search, faster HNSW builds, better faceting and aggregations, and a long list of fixes across KNN, replication, protocol compatibility and other areas.
This post is a catch-up for everything shipped from 25.0.1 through 27.1.5.
Upgrade Notes
Please review these before upgrading:
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27.0.0 adds built-in auth/authz, and enabling it changes access assumptions. Auth is not enabled by default, but once you enable it, anonymous access no longer works. Roll it out in stages: upgrade remote agents and replication peers first, then upgrade the masters that query or manage them, and enable auth only after the whole topology is on the new version. Distributed remote-agent and replication-related operations also need matching stored auth data across the participating daemons. A successful
JOIN CLUSTERreplaces the joining node's local auth data with the donor cluster's auth data. (Issue #2833, PR #3648) -
26.0.0 changed replication storage layout. Incoming replicated tables now live under the normal
data_dir/<table>layout instead of the clusterpath. If you run replication clusters with a custompath, you may need to move or re-synchronize replicated tables after upgrade. Downgrade is only safe before the new layout is adopted. (Issue #4431, PR #4598) - If you manage MCL separately from the daemon, upgrade it together with Manticore. This release line moves through several MCL updates, from vector-performance work to multithreaded HNSW builds and later stability fixes. Mixing an older library with a newer daemon is not recommended. (25.2.0, 25.15.0, 26.0.3, 26.3.2, 27.1.0)
Highlights
Built-in authentication and authorization
Manticore now supports users, passwords, bearer tokens, and fine-grained permissions across MySQL, HTTP/HTTPS, distributed remote agents, and replication-related operations. This makes access control a first-class part of the product instead of something that always has to be handled outside the database.
Sharded tables
Manticore can now create and manage sharded tables, distribute inserts across shards, and handle more of the surrounding lifecycle in one place. That makes larger write-heavy deployments easier to operate and reduces the amount of sharding-specific logic that has to live outside the engine.
Conversational search
This release adds conversational search to Manticore Search. It is exposed through CREATE CHAT MODEL and CALL CHAT, so you can ask questions over an existing vectorized table instead of building a separate retrieval layer around the same data.
Under the hood, Manticore Search runs KNN on a FLOAT_VECTOR field, builds LLM context from that field's from='...' source columns, keeps conversation history by conversation_uuid, and returns both the answer and the supporting sources. If you already keep embeddings in Manticore, this makes document Q&A and support-style assistants much easier to wire up.
Faster vector builds and KNN improvements
Vector search kept improving throughout this cycle.
Manticore improved KNN performance, added local ONNX embeddings support, sped up ONNX inference, and then made HNSW build and rebuild work much faster with multithreaded index construction.
A few important steps in that work:
- 25.1.0 improved KNN distance calculation and AVX-512 loading.
- 25.2.0 added local ONNX embeddings support in MCL and improved vector-search performance further.
- 25.14.0 and 25.15.0 added multithreaded HNSW builds together with the required library support.
The biggest practical improvement here is a much faster auto-embedding and shorter build and rebuild time for large vector tables. Initial KNN builds, chunk merges, and ALTER TABLE ... REBUILD KNN are all affected.
Better faceting and aggregations
Faceting and aggregations also became more useful.
facet_filter_mode makes it easier to build e-commerce-style filters that preserve selected, available, and unavailable buckets under active filtering.
On the analytics side:
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date_histogram()gainedtime_zoneandoffset - Opensearch dashboards support
- Manticore added statistical aggregations such as
percentiles,percentile_ranks, andmad
Other Notable Improvements
This release line also includes several smaller but useful additions:
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searchd --checkvalidates configuration before startup without side effects. -
EXIT CLUSTERlets a node leave a replication cluster online without restarting. -
dict=keywords_32kmakes it possible to index very long machine-generated tokens such as hashes and message IDs without silent truncation. - The built-in Ukrainian lemmatizer expands native morphology support for Ukrainian text search.
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Systemd
Type=notifyimproves startup and shutdown supervision. -
searchdprocess under systemd management now logs tosystemdjournal -
JOINqueries now support explicit left-table column prefixes. - OpenSearch Dashboards support.
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manticore-loadgained multi-query support.
Bug Fixes
This release line also includes 65 changelog-listed fixes. The latest follow-up releases added a few more worth calling out:
- 27.1.5 fixed a crash when fetching columnar
float_vectorattributes. - 27.1.4 fixed
ALTER TABLE ... RECONFIGUREandSHOW CREATE TABLEfor one-way upgrades fromdict='keywords'todict=keywords_32k. - 27.1.3 updated Buddy to 4.0.1 and tightened Queue-plugin mutation permission handling under auth.
- KNN-by-
doc_idqueries now preserveoffsetandmax_matchescorrectly. - KNN rescoring order was fixed, so explicit
ORDER BYtie-breakers work again. - Hybrid fused queries with
GROUP BYon columnar tables stopped crashing. - Replication and node-rejoin crash paths were cleaned up further.
- Binary MySQL protocol behavior was fixed in 25.12.1, which matters for integrations that expect real client compatibility.
- Fluent Bit bulk-ingest interoperability was fixed, preventing successful responses from being replayed as duplicate inserts.
- 27.1.2 fixed
sql_attr_multihandling for plain indexes built from multiplesourceblocks.
For the complete list, see the changelog.