Collibra vs DataHub.
Collibra and DataHub both anchor in catalog & discovery — 9 dimensions differ, 3 hold. Below: posture, coverage diff, and capability matrix.
What each is betting on.
Independent and active as of mid-2026. Founded 2008 in Brussels by VUB researchers; one of the original category-defining governance incumbents. Itself an acquirer, not a target — Raito (access management), Husprey (SQL notebook), and Deasy Labs (unstructured/AI metadata) in 2025, on top of OwlDQ (2021, now the Data Quality & Observability module). Last disclosed private valuation USD 5.25B (2021).
DataHub originated at LinkedIn (open-sourced February 2020); Acryl Data was founded 2021 by ex-LinkedIn engineers to build the managed product. Series A $21M (2022, 8VC); Series B $35M (2024, Bessemer). 2024–2025 rebrand consolidated the OSS and managed offerings under a single 'DataHub' brand, with 'DataHub Cloud' replacing the older 'Acryl Cloud' name.
Each tool's current strategic narrative, verbatim from its profile.
How each tool describes the other.
Collibra is the heavyweight governance incumbent, most directly cross-shopped with atlan (modern, UX-led, lower TCO), alation, and the OSS catalogs datahub and openmetadata (open, engineer-led, free self-host). It typically wins where formal governance, regulatory auditability, and single-vendor breadth outweigh developer ergonomics and price. Its data-quality module competes with monte-carlo, anomalo, bigeye, and soda, though those remain better for CI/pipeline-gating and dbt-native workflows.
DataHub's page doesn't directly mention Collibra. See the DataHub detail page.
Each quote is pulled from the named tool's own "Where it fits" write-up.
Spec sheet diff.
| Collibra | DataHub | |
|---|---|---|
| Vendor | Collibra | Acryl Data |
| Deployment | SaaS only | SaaS · Self-hosted |
| License | Proprietary | Open source |
| Pricing | Contact sales | OSS · free |
| Free tier | No | Yes |
| OSS self-host | No | Yes |
| dbt integration | Plugin | Native |
| Founded | 2008 | 2021 |
| HQ | Brussels, Belgium | Palo Alto, CA |
| Authoring style | SQL | YAML |
| Test paradigm | Assertion + anomaly | Assertion-based |
Both share Primary cluster: Catalog & discovery · OpenLineage: Consumer · Status: ● active
Each tool's center of gravity.
| Cluster | Collibra | DataHub |
|---|---|---|
| Quality & testing | 2/3 | 2/3 |
| Catalog & discovery | 3/3primary | 3/3primary |
| Lineage & metadata | 3/3 | 3/3 |
Scored 0–3 per cluster on the same rubric across all tools. A 0 means the cluster isn't the tool's focus, not that the feature is absent. See the methodology.
Where they cover different ground.
The declared feature set.
7 of 10 declared features differ — listed first.
These are each tool's self-declared key_features; a blank dot means
undeclared, not impossible.
| Feature | Collibra | DataHub |
|---|---|---|
| ML Anomaly Detection Quality & testing | ||
| Schema Change Detection Quality & testing | ||
| PII Auto-Classification Catalog & discovery | ||
| OpenLineage-Native Lineage & metadata | ||
| Reverse Impact Analysis Lineage & metadata | ||
| Table-Level Lineage Lineage & metadata | ||
| Transformation Lineage Lineage & metadata | ||
| Data Contracts Quality & testing | ||
| Business Glossary Catalog & discovery | ||
| Column-Level Lineage Lineage & metadata |
Where they disagree.
Quality & testing
1 of 13 differ| Collibra | DataHub | |
|---|---|---|
| dbt-native |
Catalog & discovery
1 of 9 differ| Collibra | DataHub | |
|---|---|---|
| Free self-host |
Lineage & metadata
0 of 7 differNo disagreement on any of the 7 capabilities in this cluster — they match across the board.
When to pick each.
Large, regulated enterprises — banks, insurers, pharma, public sector — that need a governance-first control plane: a real CDO function, formal stewardship, a business glossary, policy enforcement, and auditable lineage for regulations like BCBS 239, GDPR, SOX, HIPAA, and the EU AI Act. Collibra is strongest where governance process and accountability matter more than developer ergonomics, and where a single vendor for catalog plus governance plus lineage plus data quality plus AI governance is preferred over best-of-breed point tools.
Engineering-led data platforms that want an open, extensible metadata layer they can shape to their stack — with a credible managed escape hatch (DataHub Cloud) when self-hosting Kafka, Elasticsearch, and the graph store stops being fun. Particularly strong for organisations that already think in events: DataHub's Kafka-based Metadata Change Log makes it a natural fit for shops that want metadata to flow the same way data does. The SQL parser is genuinely best-in-class in the OSS catalog space, with SQLGlot-based column-level lineage benchmarked at 97–99% accuracy on standard corpora — materially better than competing parsers. A good fit also for teams wiring DataHub into AI agents via the native MCP server.
What each does best.
Collibra stands out for
- The deepest governance and stewardship tooling in the cluster — a configurable workflow engine, business glossary, policies, ownership, and audit trails purpose-built for regulated enterprises
- Broad single-vendor footprint — catalog, lineage (table and column, OpenLineage-aware), an ML data-quality module (from the OwlDQ acquisition), privacy, and AI governance under one platform
- Strong automated lineage with root-cause and downstream impact analysis at table, column, and report level, with in-line transformation context
- A mature, analyst-recognised leader with 100+ catalog integrations and a large regulated-enterprise customer base
DataHub stands out for
- Best-in-class column-level SQL lineage parser (SQLGlot-based, benchmarked at 97–99% accuracy on standard corpora)
- Event-driven Kafka MCL architecture — metadata changes are a stream, not a snapshot, which composes well with downstream consumers
- Native OpenLineage consumer endpoint plus dedicated Spark and Airflow plugins
- Open-core model with a credible managed product (DataHub Cloud) means buyers can start free and graduate without a re-platforming
Tools both also compete with.
A note on this comparison.
Every capability value above traces to Collibra or DataHub's own structured spec, which links back to its source — nothing here is averaged or smoothed across the two.
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