Atlan Lakehouse vs OpenMetadata

Atlan Lakehouse is a knowledge architecture for storing, managing, and serving context to enterprise AI agents. Its design combines a knowledge graph, Iceberg-native file storage, vector-native search, and time travel. Context is exposed through MCP, A2A, SQL, and APIs. Atlan says its agents can use the Enterprise Data Graph to create asset descriptions, connect business terms, and surface business questions. Native connectors cover data platforms, databases, BI tools, ETL pipelines, orchestrators, and data quality tools, with Snowflake, BigQuery, Tableau, dbt, and Airflow listed as examples. Connectors read metadata such as schemas, structures, lineage, ownership, and timestamps while source data remains in source systems. The App Framework lets developers, partners, and customers create custom connectors and apps with APIs, SDKs, CLI tools, and UI extension points. Atlan recommends single-tenant SaaS and lists AWS, Microsoft Azure, and Google Cloud Platform. A self-deployed runtime runs in the customer environment and requires additional enablement and licensing. Pricing is on request, and no free trial is offered.

OpenMetadata is an open-source platform for cataloging and governing data, bringing technical context, business meaning and organizational memory into a knowledge graph. Its capabilities include discovery, data quality, observability, lineage, semantics and memory. The graph connects schemas, tables, columns, dashboards, pipelines, ML models, owners and classifications. Glossary terms, metric definitions and relationships using RDF, OWL, DCAT and Schema.org help represent shared business meaning. For AI workflows, OpenMetadata provides an MCP server, an AI SDK and a Context Center for articles, documents and memories. Its ingestion framework has connectors for 130+ data services, including Airflow, BigQuery, Databricks, dbt, Kafka, MySQL, Snowflake and Tableau. The schema-first architecture includes 700+ open specifications in JSON Schema and RDF/JSON-LD. It can be deployed in an organization's own environment, explored in a live sandbox with demo data, or used through a free cloud service with the organization's data. The self-hosted plan is listed at free, with no usage limits stated. Security documentation describes stored-secret encryption, SSL/TLS connections and external secrets manager support.