Plexara vs Data Catalogs

A data catalog used to be somewhere people went to look things up. Today the reader that consults it most is an AI agent, at the moment it writes a query. Plexara keeps the catalog inside the platform the agent works through, so the work the agent does writes the catalog as it goes, and what the catalog knows arrives with every answer.

The catalog market

What dedicated catalogs do well

The established catalogs are mature products built for governance programs: hundreds of connectors, lineage extracted from ETL and BI tools, stewardship workflows, and classification at scale. Every one of them now offers a way for AI agents to read it.

Atlan: A broad connector library, active metadata and a hosted MCP server that runs each call with the signed-in user’s permissions. Vendr reports a median contract of $50,420 a year across 44 purchases.; Vendr, accessed October 29, 2026
Collibra: Enterprise stewardship, policy and classification, with an MCP server that serves governed catalog, glossary and lineage to Claude, ChatGPT, Databricks, Snowflake Cortex and Microsoft Copilot.; Collibra MCP Server
Alation: A long-established catalog for large data estates, which announced programmatic access for agents through MCP with its agentic platform in March 2025.; Alation press release, March 3, 2025
Snowflake Horizon Catalog: Column-level lineage across Snowflake, external databases, BI tools and OpenLineage feeds, with quality monitoring for what lives in Snowflake. Snowflake agreed to acquire Select Star in November 2025 to widen what Horizon sees.; Snowflake, November 24, 2025
Databricks Unity Catalog: Column-level lineage captured from notebooks, jobs, Databricks SQL and dashboards, queryable as a system table, for everything registered in the metastore.; Databricks documentation

Catalogs are also being folded into larger platforms. Salesforce completed its acquisition of Informatica, catalog and governance included, on November 18, 2025, and the Select Star agreement brings an independent catalog into Snowflake. The market is moving the catalog closer to where the work runs.

What changed

Reading the catalog is no longer the hard part

Once every catalog speaks MCP, any agent can look a table up. The harder question is whether the catalog knows about the work the agent itself does. An agent that answers questions also creates things: a table registered from a supplier’s spreadsheet, a webhook source a vendor posts to, an automation that rebuilds a dashboard every fifteen minutes.

A separate catalog learns about that work when its connectors next ingest the systems where it landed, and records lineage when the engine that ran it reports lineage. When the catalog sits inside the platform doing the work, the work writes the catalog: the registered table is cataloged before the request returns, and each automation run records an edge from every table it read to the file it wrote, naming itself as the writer.

For a company whose catalog will mostly be read by agents, that is the case for not making the catalog a separate purchase. For a company running a formal governance program, the dedicated products cover ground Plexara does not, and the table below says where.

Side by side

The middle column describes the catalogs built into the large data clouds as a group; each differs in detail.

	Dedicated catalog	Data cloud catalog	Plexara
Where it sits	A separate product beside your data platforms	Inside one data cloud	Inside the platform your agents query and your automations run on
What it covers	Hundreds of sources through prebuilt connectors, including BI and ETL tools	Deep coverage of what lives in that cloud, with some external sources	Every database, API and GraphQL connection on the platform, and every table your team or your automations create
Lineage	Extracted from many tools, often to the column	Column-level for work run in that cloud	Table to table, recorded from SQL that writes, automation runs and table registrations on the platform
Data quality and profiling	Built in or tightly integrated	Built in for that cloud’s data	Incidents raised by people and agents travel with query results; no checks or profiling
Stewardship and certification	Workflows, approval states and badges	Varies by cloud	Agent-captured knowledge passes a review queue; direct edits are permissioned and audited; no certification badges
Privacy classification	Scanners and classification at scale	Built in for that cloud’s data	Sensitivity tags set by people and agents, carried into every query result
How agents read it	The vendor’s MCP server or API	The cloud’s own assistants and MCP server	One fetch returns a table’s whole record, and every query result carries the descriptions of what it read
History	Varies by product	Varies by product	Every field versioned on its own, with the previous value and Roll back
Who operates it	The vendor, as SaaS, with your team running ingestion	The cloud provider	Deasil Works runs, upgrades and monitors it with the rest of the platform
How it is bought	Its own contract, usually quoted	Part of the cloud contract	Part of every Plexara deployment

Choosing

When each is the right call

A dedicated catalog fits when

01
A formal governance program
Stewards, councils and certification states are how the business decides what is trusted, and auditors expect to see that workflow.
02
Column lineage across many tools
Impact analysis has to follow a column from the source system through ETL jobs into dozens of BI dashboards that run outside any one platform.
03
Quality monitoring and profiling
Freshness, volume and distribution checks with alerting are part of the contract with data consumers.
04
Privacy operations at scale
Classification scanners and subject-access workflows have to cover every store the company runs.
05
One cloud holds nearly everything
When almost all of the data and the work live in one data cloud, that cloud’s own catalog sees the most with the least effort.

The platform’s catalog fits when

01
The catalog’s main reader is an agent
Descriptions, glossary terms and incidents matter most at the moment a query is written, and that is where Plexara puts them.
02
Data is spread across systems
Warehouse tables, SaaS APIs and spreadsheets people upload need one place where they are described alike.
03
The business builds as it goes
Tables, sources and automations are created every week, and the catalog should know about them the day they exist.
04
No team to run another product
Deasil runs the catalog with everything else, and curation happens in the work rather than as a separate project.

The two also run side by side. A catalog that exposes an MCP server connects through the MCP gateway, under the same roles and audit as everything else, while Plexara’s own catalog keeps describing the tables and automations created on the platform.

How the catalog itself works, from what it holds to lineage, history and what the agent reads, is on Catalog Governance.

Catalog Governance

One catalog over every connection, curated by people and agents, with lineage recorded from what runs.

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