Cloudera Data Lineage (Octopai) vs Marquez.
Cloudera Data Lineage (Octopai) and Marquez both anchor in lineage & metadata — 8 dimensions differ, 1 hold. Below: posture, coverage diff, and capability matrix.
What each is betting on.
Acquired by Cloudera in November 2024 (originally Octopai, founded 2016 in Israel). Continues to ship as a distinct SaaS product line under the brand 'Cloudera Data Lineage' — also marketed as 'Cloudera Octopai Data Lineage.' First major Cloudera-era release tagged 1.0.0 in October 2025; Spark Connector added June 2025. Available on AWS Marketplace and Azure Marketplace as a standalone purchase, even outside Cloudera deployments.
LF AI & Data graduated project, Apache-2.0. The reference implementation of the OpenLineage standard. Active development continues; Astronomer is the largest contributor (Datakin, the original commercial sponsor, was acquired by Astronomer in 2022 and folded into managed Airflow). No managed Marquez Cloud offering exists in 2026 — self-host or don't run it.
Each tool's current strategic narrative, verbatim from its profile.
How each tool describes the other.
The honest test is whether the connector library actually covers your estate at the depth claimed, and whether the 24-hour deploy holds when integration realities (auth, network, source-system credentials) hit. Run a paid proof-of-concept on a meaningful subset — three legacy systems, two BI tools, your warehouse — and look at: did column-level lineage resolve through every source, was the cross-tool stitching accurate, and did the reverse-impact analysis answer the regulatory question your team actually has? If yes, the product earns its premium relative to running a Marquez backend with manual emitters; if no, the connector breadth is less valuable than the marketing implies.
Marquez's page doesn't directly mention Cloudera Data Lineage (Octopai). See the Marquez detail page.
Each quote is pulled from the named tool's own "Where it fits" write-up.
Spec sheet diff.
| Cloudera Data Lineage (Octopai) | Marquez | |
|---|---|---|
| Vendor | Cloudera | Marquez Project |
| Deployment | SaaS only | Self-hosted only |
| License | Proprietary | Open source |
| Pricing | Contact sales | OSS · paid tiers |
| Free tier | No | Yes |
| OSS self-host | No | Yes |
| dbt integration | None | Plugin |
| OpenLineage | None | Native |
| Founded | 2016 | 2018 |
| HQ | Santa Clara, CA | — |
| Status | ○ acquired | ● active |
Both share Primary cluster: Lineage & metadata
Each tool's center of gravity.
| Cluster | Cloudera Data Lineage (Octopai) | Marquez |
|---|---|---|
| Catalog & discovery | 2/3 | 1/3 |
| Quality & testing | 0/3 | 0/3 |
| Lineage & metadata | 3/3primary | 3/3primary |
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 6 declared features differ — listed first.
These are each tool's self-declared key_features; a blank dot means
undeclared, not impossible.
| Feature | Cloudera Data Lineage (Octopai) | Marquez |
|---|---|---|
| PII Auto-Classification Catalog & discovery | ||
| OpenLineage-Native Lineage & metadata | ||
| Reverse Impact Analysis Lineage & metadata | ||
| Column-Level Lineage Lineage & metadata | ||
| Table-Level Lineage Lineage & metadata | ||
| Transformation Lineage Lineage & metadata |
Where they disagree.
Catalog & discovery
5 of 9 differ| Cloudera Data Lineage (Octopai) | Marquez | |
|---|---|---|
| Business glossary | ||
| PII auto-classify | ||
| Tag propagation | ||
| Ownership tracking | ||
| Free self-host |
Lineage & metadata
2 of 7 differ| Cloudera Data Lineage (Octopai) | Marquez | |
|---|---|---|
| Reverse impact | ||
| BI lineage |
When to pick each.
Mid-market and enterprise data teams who want cross-system column-level lineage spanning legacy ETL, BI tools, and cloud warehouses, but who do not want to procure IBM-scale software. The 24-hour deploy claim — no professional services required — is genuine for SaaS deployments, and the connector library covers the same hybrid estate Manta does at a generally lower price point. Especially defensible if you're already a Cloudera shop, where it ships as a fabric component, but the standalone SaaS purchase via AWS or Azure Marketplace is a real path for non-Cloudera buyers too.
Data platform teams who want a vendor-neutral lineage substrate under existing pipeline tooling, especially Airflow plus Spark plus dbt shops where OpenLineage providers are already shipping events. Strong fit when the operating principle is "open standard, no vendor lock-in" rather than "polished UI for business users." Also a defensible choice for organisations that already run a heavy catalog (Atlan, DataHub, OpenMetadata) and want lineage events flowing into both for redundancy or re-use, since OpenLineage is fundamentally a producer-consumer protocol — multiple backends can subscribe.
What each does best.
Cloudera Data Lineage (Octopai) stands out for
- 60+ native connectors covering ETL (Informatica, SSIS, Talend), BI (Tableau, Power BI, Cognos, MicroStrategy), and modern warehouses
- SaaS-only deployment with a credible 24-hour time-to-value claim — no professional services bundled in
- Available on AWS Marketplace and Azure Marketplace as a standalone purchase, even outside Cloudera deployments
- Cross-system column-level lineage with reverse impact analysis — comparable scanner depth to Manta
Marquez stands out for
- The reference implementation of OpenLineage — interoperability with the standard is its native shape, not a marketing claim
- Apache-2.0 with no enterprise-only features held back; what you self-host is what exists, full stop
- LF AI & Data graduated project — governance is institutional, not single-vendor
- Column-level lineage flowing through from the Spark integration (since Marquez 0.27 / OpenLineage 0.9)
Tools both also compete with.
A note on this comparison.
Every capability value above traces to Cloudera Data Lineage (Octopai) or Marquez's own structured spec, which links back to its source — nothing here is averaged or smoothed across the two.
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