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.
Please review these before upgrading:
JOIN CLUSTER replaces the joining node's local auth data with the donor cluster's auth data. (Issue #2833
, PR #3648
)data_dir/<table>
layout instead of the cluster path. If you run replication clusters with a custom path, 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
)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.
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.
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.
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:
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.
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:
date_histogram()
gained time_zone and offsetpercentiles, percentile_ranks, and madThis release line also includes several smaller but useful additions:
searchd --check
validates configuration before startup without side effects.EXIT CLUSTER
lets a node leave a replication cluster online without restarting.dict=keywords_32k
makes it possible to index very long machine-generated tokens such as hashes and message IDs without silent truncation.Type=notify
improves startup and shutdown supervision.searchd process under systemd management now logs to systemd journalJOIN queries now support explicit left-table column prefixes.manticore-load gained multi-query support.This release line also includes 65 changelog-listed fixes. The latest follow-up releases added a few more worth calling out:
float_vector attributes.ALTER TABLE ... RECONFIGURE and SHOW CREATE TABLE for one-way upgrades from dict='keywords' to dict=keywords_32k.doc_id queries now preserve offset and max_matches correctly.ORDER BY tie-breakers work again.GROUP BY on columnar tables stopped crashing.sql_attr_multi handling for plain indexes built from multiple source blocks.For the complete list, see the changelog .
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