Google Cloud Knowledge Catalog vs. Atlan
A side-by-side comparison based on G2 review data.
| Metric | Google Cloud Knowledge Catalog | Atlan |
|---|---|---|
| Overall rating | 4.3 | 4.5 |
| Review count | 17 | 135 |
| Ease of use | 8.7 | 9.1 |
| Ease of setup | 10.0 | 9.3 |
| Quality of support | 8.5 | 9.3 |
| Meets requirements | 9.0 | 8.8 |
| NPS | 58.823529 | 67.407407 |
| Small Business | 41.2% | 7.4% |
| Mid-Market | 17.6% | 50.4% |
| Enterprise | 41.2% | 42.2% |
| Total page views | 69 | 1,350 |
| Total LLM citations | 152 | 12,571 |
Google Cloud Knowledge Catalog
Knowledge Catalog is a dynamic, always-on, universal context engine for agents. It unifies structured, unstructured, and SaaS data into a governed, agent-ready truth. Knowledge Catalog aggregates native context across your Google and partner data platforms, semantic models, and third-party catalogs, unifying them into a single, governed source of truth. Automatically harvest technical metadata across your foundational systems—including BigQuery, AlloyDB, Spanner, Cloud SQL, Firestore (Preview), and Looker (Preview).
Atlan
Atlan is the context layer for enterprise AI. It continuously reads your warehouses, databases, pipelines, BI tools, and business systems to reverse construct an enterprise data graph that captures assets, lineage, entities, metrics, policies, and relationships. On top of that graph, it enriches and curates machine-readable semantics — descriptions, popular joins, KPI and metric definitions, ontologies, and business rules — and organizes them into governed, versioned context repos: bounded bundles of context that reflect how your company defines key concepts and makes decisions.
- Ease of Use
- Features
- User Interface
- Easy Setup
- Data Cataloging
- Integrations