OpenMetadata vs Secoda.
OpenMetadata and Secoda both anchor in catalog & discovery — 4 dimensions differ, 3 hold. Below: posture, coverage diff, and capability matrix.
What each is betting on.
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).
Acquired by Atlassian; announced via Secoda's blog (Dec 4, 2025) and reported by TechTarget (Dec 5, 2025). Terms undisclosed. Atlassian plans to fold Secoda's semantic cataloging into its Teamwork Graph / Rovo AI and migrate it onto the Atlassian Cloud Platform over time. As of mid-2026 Secoda still operates under its own brand with the founding team aboard; near-term customer experience is said to be unchanged. Founded 2021 in Toronto (Y Combinator); ~USD 14M Series A in 2023.
Each tool's current strategic narrative, verbatim from its profile.
How each tool describes the other.
OpenMetadata's page doesn't directly mention Secoda. See the OpenMetadata detail page.
Secoda cross-shops most directly with atlan, datahub, and openmetadata as a catalog/discovery plane, and with unity-catalog for teams already on Databricks. Against Atlan it positions as faster-to-value, lighter-weight, and more self-serve for mid-market teams; against the OSS catalogs it trades open-source portability for a polished AI-first UX and bundled observability. It is not a dedicated data-quality engine like monte-carlo, anomalo, or soda — its monitoring is consolidated and metadata-driven rather than deep test authoring, which is why we score the quality-testing cluster zero.
Each quote is pulled from the named tool's own "Where it fits" write-up.
Spec sheet diff.
| OpenMetadata | Secoda | |
|---|---|---|
| Vendor | Collate | Secoda (Atlassian) |
| License | Open source | Proprietary |
| Pricing | OSS · free | Contact sales |
| Free tier | Yes | No |
| OSS self-host | Yes | No |
| HQ | Saratoga, CA | Toronto, Ontario, Canada |
| Status | ● active | ○ acquired |
Both share Primary cluster: Catalog & discovery · Deployment: SaaS · Self-hosted · dbt integration: Native · OpenLineage: None · Founded: 2021
Each tool's center of gravity.
| Cluster | OpenMetadata | Secoda |
|---|---|---|
| Quality & testing | 2/3 | 0/3 |
| 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.
5 of 8 declared features differ — listed first.
These are each tool's self-declared key_features; a blank dot means
undeclared, not impossible.
| Feature | OpenMetadata | Secoda |
|---|---|---|
| Data Contracts Quality & testing | ||
| Schema Change Detection Quality & testing | ||
| Reverse Impact Analysis Lineage & metadata | ||
| Table-Level Lineage Lineage & metadata | ||
| Transformation Lineage Lineage & metadata | ||
| Business Glossary Catalog & discovery | ||
| PII Auto-Classification Catalog & discovery | ||
| Column-Level Lineage Lineage & metadata |
Where they disagree.
Catalog & discovery
2 of 9 differ| OpenMetadata | Secoda | |
|---|---|---|
| Data contracts | ||
| Free self-host |
Lineage & metadata
1 of 7 differ| OpenMetadata | Secoda | |
|---|---|---|
| Historical |
When to pick each.
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.
Mid-market and scaleup data teams that want one AI-native tool covering catalog, search, lineage, documentation, and basic observability rather than running separate catalog, lineage, and monitoring tools — especially teams that value a natural-language assistant for self-serve data questions and broad business-user adoption. A strong fit for organisations on Snowflake, BigQuery, or Databricks plus dbt and a modern BI tool who want fast time-to-value and lighter governance overhead than enterprise suites like Atlan or Collibra.
What each does best.
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)
Secoda stands out for
- AI-native search and assistant as the primary interface — natural-language data questions across the catalog, plus purpose-built agents for search, documentation, observability, and governance
- Consolidated — catalog, data dictionary/glossary, column- and table-level lineage, governance, and no-code monitoring in one workspace
- Strong automated lineage including column-level, BI-tool coverage, impact analysis, and downstream/upstream owner notifications
- Fast time-to-value and broad business-user adoption relative to heavyweight enterprise catalogs, with 50+ no-code connectors
Tools both also compete with.
A note on this comparison.
Every capability value above traces to OpenMetadata or Secoda's own structured spec, which links back to its source — nothing here is averaged or smoothed across the two.
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