Data Mesh Platform

Data Mesh Infrastructure That Actually Scales

Built for platform engineers implementing domain-driven architecture. DataHub gives your domains real ownership, enforced contracts, and federated governance.

  • Organize assets into domains with nested hierarchies and clear ownership
  • Enforce data contracts across schema, freshness, and quality SLAs
  • Federated governance with centralized standards, distributed execution
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See DataHub govern your Data Mesh

A DataHub engineer will scope the session to your environment.

Trusted by modern data teams
The hard part

Why most Data Mesh rollouts stall

Domains go live. Governance doesn't follow. Platform engineers inherit the gap.

Ownership without accountability

Domains are declared but never enforced. No one knows who is responsible when a dataset breaks or goes stale.

Contracts that live in Confluence

Data contracts written in wikis are invisible to pipelines. Violations surface in production, not at authoring time.

Governance that doesn't scale

Central teams can't review every domain change. Policies written once become stale as the mesh grows across teams.

Discovery that stays centralized

Consumers can't find domain data products without asking the platform team. Self-service never materializes in practice.

The platform

A better way to implement Data Mesh

DataHub gives platform engineers the primitives to make domain ownership real, contracts enforceable, and governance federated by design.

Domain-driven data organization

Group assets into domains with nested hierarchies, assigned owners, and clear boundaries. Ownership is tracked in the metadata layer, not a spreadsheet.

  • Nested domain hierarchies with inherited ownership
  • Assign stewards and owners at the asset level
  • Propagate domain context across lineage automatically

Data products as first-class citizens

Model data products in the catalog with documented interfaces, SLAs, and consumers. Producers and consumers have a shared, versioned contract surface.

  • Register data products with owners and SLA metadata
  • Track consumers and downstream dependencies
  • Surface product health and usage in one view

Data contracts and quality monitoring

Define contracts on schema, freshness, and quality thresholds. DataHub monitors assertions continuously and surfaces violations before consumers are affected.

  • Schema, freshness, and volume assertions built in
  • Contract violations routed to domain owners directly
  • Integrates with Great Expectations and dbt tests

Federated governance at scale

Set platform-wide policies centrally. Domain teams execute them locally. Access control, classification, and lineage propagate automatically without central bottlenecks.

  • Role-based access control scoped to domain boundaries
  • Automated classification propagated across lineage
  • Audit trails per domain for compliance reporting
How it works

How it works

Three steps from existing infrastructure to a governed Data Mesh. No pipeline rebuilds required.

Connect your data sources

Ingest from Snowflake, BigQuery, dbt, and 80+ sources
No pipeline rebuilds -- connectors run against your existing stack
Metadata ingestion via Python SDK, YAML, or REST API

Define domains and contracts

Group assets into domains with owners and nested hierarchies
Register data products with SLA and interface metadata
Author contracts on schema, freshness, and quality thresholds

Activate governance everywhere

Policies propagate to every domain without manual review
Contract violations surface to owners before consumers see them
Lineage and audit trails available across every domain
Enterprise scale

Built for enterprise-grade Data Mesh scale

Deploy on your infrastructure. Integrate with your existing tools. Extend via open APIs.

Integrations

Snowflake, BigQuery, Databricks, dbt
Looker, Great Expectations, Airflow
80+ pre-built connectors across the modern data stack

Deployment

Kubernetes, AWS, and GCP supported
YAML and GitOps-compatible configuration
Apache 2.0 licensed -- no vendor lock-in

APIs and extensibility

GraphQL and REST APIs for full programmatic control
Python SDK for ingestion and metadata automation
Custom metadata models via the Metadata Service
Peer insights

Trusted by modern data teams

Gartner Peer Insights

Engineer, Services, 1B-10B revenue

Verified review

Gartner Peer Insights, 2024

"DataHub gave our platform team the ability to assign real ownership to domains and enforce it. We stopped chasing people in Slack to find out who owned a dataset."

Platform Engineer

Services industry, 1B-10B revenue

FAQ

Frequently asked questions about Data Mesh

Implementation complexity depends on your existing stack and how many domains you are standing up. DataHub connects to your existing sources via pre-built connectors, so you are not rebuilding pipelines. Most teams start with a single domain to validate the ownership and contract model before expanding. The Python SDK and YAML-based configuration are designed for platform engineers who already work in code.
The platform team sets policies centrally in DataHub -- classification rules, access control standards, and compliance requirements. Domain teams execute those policies locally against their own assets. DataHub propagates policy enforcement automatically through lineage, so central teams do not need to review every domain change. Audit trails are available per domain for compliance reporting.
Data contracts in DataHub are assertions attached to a dataset or data product. You define thresholds for schema structure, row freshness, volume, and custom quality checks. DataHub monitors those assertions continuously and surfaces violations in the catalog, routing alerts to the domain owner. Contracts integrate with existing test frameworks including dbt tests and Great Expectations.
DataHub ships with 80+ pre-built connectors covering warehouses, lakes, BI tools, orchestrators, and transformation frameworks. Supported sources include Snowflake, BigQuery, Databricks, dbt, Looker, Airflow, and Great Expectations. If your source is not covered, the Python SDK and REST API allow you to push metadata from any system.
Timeline depends on the number of sources you are ingesting and the complexity of your ownership model. A single domain with two or three sources can be ingested and organized within a few days. Defining contracts and governance policies takes longer and depends on how much alignment already exists across your teams. DataHub does not require a full mesh rollout before you see value -- most teams start with one domain and expand incrementally.

Ready to implement Data Mesh at scale?

DataHub gives your domains real ownership, enforced contracts, and governance that holds across every team and source in your stack.

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Scoped to your environment Apache 2.0 open source No vendor lock-in
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