Metadata Tool Consolidation

Four capabilities on one metadata foundation

Lineage, catalog, governance, and semantics read from and write to the same metamodel. A stewardship decision shows up in lineage the moment it's made, with no integration job in between.

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Key capabilities

One fully integrated platform built on a shared metamodel

400+ connectors across legacy, cloud, and hybrid sources

Version and configuration management across all four capabilities

Nearly 30 years of OEM metadata engineering

The Problem

The integration became its own product

Most enterprises run separate tools for lineage, catalog, governance, and semantics. None of them share a metamodel.

So someone builds custom integration between them, and that integration acquires a backlog, an owner, and a maintenance cost of its own.

Every change in one system needs manual synchronization across the others. The team ends up maintaining plumbing while the estate drifts underneath it.

An assembled metadata solution carries this structurally. Tools that each own their own metadata will always need something in between them.

The Approach

One metamodel underneath all four capabilities

Data Lineage, Data Catalog, Data Governance, and Semantic Hub are built on a shared metadata foundation. Lineage edges, catalog entries, governance policies, and semantic definitions all read from and write to the same underlying model.

A stewardship decision is visible in lineage immediately. A catalog update is reflected in the definitions that reference it. Synchronization drops out of the picture, because there's one copy from the start.

Version and configuration management runs across all four, so the estate carries one change history that every capability writes to.

The catalog can't drift from the estate it describes.

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What Changes

Fewer tools, one change history

Consolidating lineage, catalog, governance, and semantics removes the integration surface between them.

Coverage that reaches the legacy systems

400+ connectors span mainframe and legacy sources through modern cloud platforms, so no part of the estate sits outside the repository.

A platform you can leave

Remove us tomorrow. Your definitions stay.

Fix business logic at the foundation

MetaKarta establishes the shared metadata foundation organizations have been trying to patch together for years: trusted BI, reliable AI, and defensible governance, compiled into every architecture, every cloud, and every tool. No runtime dependency. No vendor lock-in. No greenfield start required.

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Frequently asked
questions

What does "one metamodel" mean day to day?

Lineage edges, catalog entries, governance policies, and semantic definitions are records in the same shared metadata repository. When a steward certifies a term, lineage and every definition that references it show the change immediately, with no sync job in between.

Can we start alongside the tools we already run?

Yes. MetaKarta connects to what's already deployed, so lineage and catalog coverage can start next to your current stack. Each replacement happens when its renewal date or its integration cost makes the case.

Does coverage reach our legacy systems?

400+ connectors span mainframe and legacy sources through Snowflake, Databricks, and the major BI platforms. The Connector Explorer lists every supported source and target, so your team can check its own estate before the first call.

What changes for the team that maintains the integrations?

The scripts and sync jobs between lineage, catalog, and governance tools go away, along with their backlog. Version and configuration management runs across all four capabilities, so there's one change history to maintain and one to audit.

Whose technology is this built on?

Meta Integration has spent nearly 30 years building metadata connectors and metadata repository technology that other vendors embed in their own products, including Microsoft Purview, Informatica from Salesforce, IBM, Oracle, and Qlik Talend. MetaKarta runs on that same metadata model.

How do we make the case to finance?

Put the full cost of the current stack on the table: licenses for three to five separate tools, plus the engineering time spent keeping them in sync, plus the cost of the next incident that slips through the gaps between them. Consolidation removes the license overlap and the integration work together.

Are we locked in once everything lives in MetaKarta?

Definitions compiled by MetaKarta are native artifacts in your warehouse and BI tools, and they keep running without MetaKarta. The semantic models are written in SHL, a YAML-based language, and version in your own Git repository.