Data Stack Index / v 02.06
Verified 2026·07·03
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Compare Same primary cluster · Catalog & discovery

Amundsen vs Atlan.

Amundsen and Atlan both anchor in catalog & discovery — 8 dimensions differ, 1 hold. Below: posture, coverage diff, and capability matrix.

Same Catalog & discovery (primary)
Differ on DeploymentLicensePricing transparencyFree tierOSS optiondbt depthWarehouse coverageLineage depth
1 ● Amundsen leads
3 shared
11 Atlan leads ○
● Amundsen

The Lyft-born OSS catalog that invented search-first discovery — historically important, but development has largely stalled since 2024.

○ Atlan

Enterprise catalog and governance plane positioned as the AI context layer — connectors, lineage, contracts, and an MCP server for agents.

● Pick Amundsen if

Teams that already run Amundsen and need to understand what they have, or teams with a genuinely minimal requirement — usage-ranked table search and ownership tracking, nothing more — who are comfortable owning a codebase that is no longer moving.

○ Pick Atlan if

Mid-market and enterprise organisations with a real data-governance function — a CDO, stewards, a defined glossary programme — who need a polished, integration-rich catalog with strong column-level lineage and an opinionated view of how AI agents should consume metadata.

01
Strategic posture

What each is betting on.

● Amundsen

Honest read: maintenance mode. Created at Lyft, open-sourced October 2019, joined LF AI & Data as an incubation project in August 2020. Development has slowed to near-zero — the last release was databuilder 7.5.1 (August 2024) and the last commit to the monorepo (April 2025) moved a maintainer to emeritus status. Stemma, the managed-Amundsen company founded by an Amundsen co-creator, was acquired by Teradata in 2023 and discontinued as a standalone product. The repo is not archived, but treat this as software that is no longer evolving.

● Atlan

Series C ($105M, May 2024) led by GIC and Meritech at a ~$750M valuation. Through 2025–2026 repositioned around 'The Context Layer for AI' — Iceberg-native metadata lakehouse, MCP server for AI agents, Context Engineering Studio. Named a Gartner MQ and Forrester Wave leader 2025. Heavy enterprise positioning; no self-serve free tier.

Each tool's current strategic narrative, verbatim from its profile.

02
At a glance

Spec sheet diff.

Amundsen Atlan
Vendor LF AI & Data Foundation Atlan
Deployment Self-hosted only Hybrid
License Open source Proprietary
Pricing OSS · paid tiers Contact sales
Free tier Yes No
OSS self-host Yes No
dbt integration Plugin Native
HQ Singapore

Full Amundsen pricing → Full Atlan pricing →

Both share Primary cluster: Catalog & discovery · OpenLineage: Consumer · Founded: 2019 · Status: ● active

03
Cluster strength

Each tool's center of gravity.

Cluster Amundsen Atlan
Lineage & metadata 1/3 3/3
Quality & testing 0/3 0/3
Catalog & discovery 3/3primary 3/3primary
▲ Asymmetry
Atlan scores 3/3 on Lineage & metadata; Amundsen scores 1/3. If this cluster is the buying motion, the choice is largely made — see the Atlan capability detail.

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.

04
Coverage

Where they cover different ground.

Target personas
Both Data engineer
Only Amundsen Analyst · Platform engineer
Only Atlan Analytics engineer · CDO · Data steward · Governance lead
Company size fit
Both Mid-market
Only Amundsen Scaleup
Only Atlan Enterprise
Warehouse coverage
Both Athena · BigQuery · Databricks · MSSQL · MySQL · Postgres · Redshift · Snowflake · Trino
Only Atlan Fabric · Synapse
Orchestrators
Both Airflow · dbt Core
Only Atlan Astronomer · Dagster · Fivetran · Prefect · dbt Cloud
05
Declared features

The declared feature set.

6 of 6 declared features differ — listed first. These are each tool's self-declared key_features; a blank dot means undeclared, not impossible.

Feature Amundsen Atlan
Data Contracts Quality & testing
Business Glossary Catalog & discovery
PII Auto-Classification Catalog & discovery
Column-Level Lineage Lineage & metadata
OpenLineage-Native Lineage & metadata
Table-Level Lineage Lineage & metadata
06
Capability matrix

Where they disagree.

Catalog & discovery

8 of 9 differ
Amundsen Atlan
Business glossary
NL search
Data contracts
Governance flows
Access requests
PII auto-classify
Tag propagation
Free self-host
Both also haveOwnership tracking

Lineage & metadata

4 of 7 differ
Amundsen Atlan
Column-level
Cross-system
Reverse impact
Historical
Both also haveBI lineage · Lineage API
Neither doesLineage diff
07
Verdict

When to pick each.

● Pick Amundsen if

Teams that already run Amundsen and need to understand what they have, or teams with a genuinely minimal requirement — usage-ranked table search and ownership tracking, nothing more — who are comfortable owning a codebase that is no longer moving. The core idea still holds up: index tables, dashboards, and people into Elasticsearch, rank results by query-log usage so the tables analysts actually trust float to the top, and keep the UX focused on the single question "which table should I use?" Databuilder's pull model is plain Python, so extending it from an existing Airflow deployment is straightforward for a data platform team.

○ Pick Atlan if

Mid-market and enterprise organisations with a real data-governance function — a CDO, stewards, a defined glossary programme — who need a polished, integration-rich catalog with strong column-level lineage and an opinionated view of how AI agents should consume metadata. Particularly strong for teams already on a modern stack (Snowflake or Databricks plus dbt plus Looker or Tableau) where Atlan's SQL parser and OpenLineage ingestion can light up lineage with relatively little manual work. The 2025 MCP-server pitch lands well for organisations actively wiring up Claude, Cursor, or internal agents and wanting a single governed surface those agents query for context.

08
Strengths

What each does best.

Amundsen stands out for

  • [+] Pioneered usage-ranked, search-first discovery — PageRank-style ranking from query logs remains a genuinely good idea that successors copied
  • [+] Deliberately small surface area — analysts get table search, owners, column stats, and previews without a governance platform's learning curve
  • [+] Apache-2.0 under neutral LF AI & Data governance, with nothing held back for a paid tier
  • [+] Databuilder is plain-Python ETL — custom extractors are easy to write and schedule from an existing Airflow deployment

Atlan stands out for

  • [+] Polished UX and onboarding — consistently scores top in analyst rankings on time-to-value relative to peers
  • [+] Lineage built from four signal sources (SQL parsing, native APIs, OpenLineage events, manual) gives broad coverage without forcing one approach
  • [+] Iceberg-native 'Metadata Lakehouse' architecture (rolled out in 2025) decouples metadata storage from compute and supports versioned/time-travel views
  • [+] First-class MCP server and AI-agent context surface — the 2025 repositioning is real product, not just marketing
09
Other alternatives

Tools both also compete with.

All Amundsen alternatives, scored →All Atlan alternatives, scored →

A note on this comparison.

Every capability value above traces to Amundsen or Atlan's own structured spec, which links back to its source — nothing here is averaged or smoothed across the two.

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