DataHub vs OpenMetadata.
DataHub and OpenMetadata both anchor in catalog & discovery — 4 dimensions differ, 7 hold. Below: posture, coverage diff, and capability matrix.
What each is betting on.
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.
Collate founded 2021 by Suresh Srinivas (ex-Hortonworks co-founder, Hadoop committer) and Sriharsha Chintalapani (Apache Kafka and Storm PMC, ex-Uber). The OpenMetadata project was launched alongside the company. Series A $10M July 2025. Differentiator vs DataHub: deliberately simpler architecture (Postgres or MySQL + Elasticsearch — no Kafka, no graph DB) and faster shipping cadence on governance features through 2024–2025 (Multi-Domain, Data Contracts GA in 1.9, Data Quality as Code).
Each tool's current strategic narrative, verbatim from its profile.
How each tool describes the other.
Against openmetadata, the trade is architecture and audience. DataHub's stack (Kafka + graph DB) is heavier to operate but more event-native. OpenMetadata's stack (Postgres + Elasticsearch) is simpler to run but pull-only. DataHub's lineage parser is technically stronger; OpenMetadata ships features faster (Multi-Domain, Data Contracts GA, Data Quality as Code all landed quickly through 2024–2025). Engineering-led shops tend to pick DataHub; steward-led shops tend to pick OpenMetadata.
Against datahub, the trade is architecture and shipping velocity. DataHub has the stronger SQL parser and the more event-native architecture; OpenMetadata has the simpler stack to operate and the faster governance feature cadence. Engineering-led shops tend to pick DataHub; steward-led and operationally-constrained shops tend to pick OpenMetadata.
Each quote is pulled from the named tool's own "Where it fits" write-up.
Spec sheet diff.
| DataHub | OpenMetadata | |
|---|---|---|
| Vendor | Acryl Data | Collate |
| OpenLineage | Consumer | None |
| HQ | Palo Alto, CA | Saratoga, CA |
| Authoring style | YAML | Code-first + GUI |
| Test paradigm | Assertion-based | Assertion + anomaly |
Both share Primary cluster: Catalog & discovery · Deployment: SaaS · Self-hosted · License: Open source · Pricing: OSS · free · Free tier: Yes · OSS self-host: Yes · dbt integration: Native · Founded: 2021 · Status: ● active
Each tool's center of gravity.
| Cluster | DataHub | OpenMetadata |
|---|---|---|
| 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.
3 of 7 declared features differ — listed first.
These are each tool's self-declared key_features; a blank dot means
undeclared, not impossible.
| Feature | DataHub | OpenMetadata |
|---|---|---|
| PII Auto-Classification Catalog & discovery | ||
| OpenLineage-Native Lineage & metadata | ||
| Table-Level Lineage Lineage & metadata | ||
| Data Contracts Quality & testing | ||
| Schema Change Detection Quality & testing | ||
| Business Glossary Catalog & discovery | ||
| Column-Level Lineage Lineage & metadata |
Where they disagree.
Quality & testing
2 of 13 differ| DataHub | OpenMetadata | |
|---|---|---|
| ML anomaly detection | ||
| Root-cause UI |
Catalog & discovery
0 of 9 differNo disagreement on any of the 9 capabilities in this cluster — they match across the board.
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.
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.
Teams that want an OSS catalog without the operational weight of DataHub's Kafka and graph-DB architecture. OpenMetadata's simpler stack — Postgres or MySQL plus Elasticsearch, no graph DB, no Kafka — makes it materially easier to stand up and keep alive. Particularly strong for shops that want one tool to cover discovery, governance, lineage, profiling, and quality together rather than glue several together. Connector breadth (120+) is the highest of the OSS catalogs, and the cadence of governance features in 2024–2025 (Multi-Domain, Data Contracts GA in 1.9, Data Quality as Code) has been faster than the competition.
What each does best.
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
OpenMetadata stands out for
- Highest connector count in the OSS catalog space (120+) — particularly strong on dashboards, ML, and pipeline systems
- Deliberately simple architecture (no Kafka, no graph DB) makes self-hosting realistic for smaller platform teams
- Unified scope — discovery, lineage, governance, quality, contracts, and collaboration in one project, not a constellation of subsystems
- Faster shipping cadence on governance features through 2024–2025 (Multi-Domain, Data Contracts GA, Data Quality as Code, Auto-Tune)
Tools both also compete with.
A note on this comparison.
Every capability value above traces to DataHub or OpenMetadata's own structured spec, which links back to its source — nothing here is averaged or smoothed across the two.
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