Atlan

Atlan launched as a modern data catalog and collaborative workspace designed to sit on top of cloud data stacks and solve metadata fragmentation. Founded to address the gap between catalogs that only indexed schemas and teams that needed context, Atlan positions itself as a workspace where lineage, business glossaries, and ownership live together. The platform emphasizes connecting to a broad set of sources and making metadata actionable inside the tools analysts already use. Atlan’s core value proposition is to reduce time-to-insight by making data discoverable, documented, and governed without heavyweight deployment overhead.

Atlan’s feature set centers on automated metadata ingestion, interactive lineage, and collaboration. Its metadata engine ingests schemas, tables, columns, and query logs from sources such as Snowflake, BigQuery, Databricks, Apache Airflow, and Looker, consolidating automated tags and usage metrics. The lineage view shows column-to-column and job-to-table traceability across pipelines so teams can troubleshoot downstream impacts. Atlan also includes an enterprise glossary and attribute-based access controls (ABAC) integrated with SSO; the platform records ownership, SLA, and certification badges per dataset. Collaboration features include in-product notes and Slack integration, where users can surface dataset cards and certification status directly in channels.

Pricing is available as a freemium entry level with pay-as-you-scale commercial tiers and custom enterprise pricing. The Free tier supports basic metadata ingestion and a limited number of tracked assets (suitable for proof-of-concept and small teams). Paid tiers (named Team/Business levels) unlock automated lineage across more sources, SLA and certification workflows, role-based access control, and audit logs; these plans are priced per seat or per asset and require contacting sales for exact monthly rates for medium to large deployments. Enterprise customers receive custom security controls, deployment options (SaaS or private cloud), and a negotiated invoice-based contract for wider usage and premium support.

Atlan is used across analytics and data governance workflows by roles like data engineers who map lineage and troubleshoot pipeline failures, and analytics managers who curate certified datasets for analysts. For example: a Data Engineer uses Atlan to trace a failing batch job’s downstream impacted tables and reduce MTTD (mean time to diagnosis), while a Data Steward uses certification badges and glossary terms to maintain regulatory compliance across datasets. Typical workflows include onboarding new data sources, running impact analysis, and centralizing business definitions. Compared against a competitor like Collibra, Atlan is often chosen for teams that prioritize embedded collaboration and direct integrations with modern cloud data platforms.