Key features
- Unified catalog — APAC tables, dashboards, ML models, pipelines, and storage catalogued in a single platform
- Automated lineage — dbt, Airflow, and query-based APAC end-to-end lineage with column-level granularity
- Data quality tests — completeness, uniqueness, custom SQL tests with historical tracking for APAC data assets
- Collaboration — APAC data asset reviews, announcements, and access request workflows
- Data profiling — automatic column-level statistics and sample data for APAC catalogued tables
- 80+ connectors — Snowflake, BigQuery, Databricks, Redshift, dbt, Airflow, Tableau, Kafka, and more for APAC stacks
- Teams and roles — APAC data ownership, stewardship, and domain-based governance with RBAC
Best for
- APAC data and analytics teams of 5-50 people who need a full-featured data catalog with lineage and quality — without commercial catalog licensing costs (Collibra at $100K+/year, Alation at $60K+/year)
- Engineering organisations using dbt for APAC data transformations who want dbt lineage and test results surfaced in a searchable catalog without manual documentation maintenance
- APAC data platform teams building self-service analytics who need data discovery, quality scoring, and access request workflows for business analysts without direct warehouse access
- APAC enterprises in regulated industries who need lineage documentation for compliance but cannot justify commercial catalog cost for initial governance program deployment
Limitations to know
- ! Self-hosted operational burden — OpenMetadata requires running OpenMetadata server, Airflow, Elasticsearch, and MySQL; APAC teams without dedicated platform capacity should evaluate OpenMetadata Cloud managed offering
- ! Smaller connector ecosystem vs DataHub — OpenMetadata has 80+ connectors vs DataHub's 70+, but specific APAC enterprise connectors (Oracle, SAP, mainframe systems) may have less mature integration support than commercial alternatives
- ! Enterprise features in development — some APAC enterprise features (advanced RBAC, SSO with enterprise IdPs, audit logging depth) are more mature in commercial alternatives; evaluate against APAC compliance requirements before committing
- ! Community size vs DataHub — OpenMetadata has an active but smaller community than DataHub; APAC teams should assess GitHub activity and Slack community health before selecting as primary metadata platform
About OpenMetadata
OpenMetadata is a fully open-source unified metadata platform (Apache 2.0 licensed) that provides APAC data and analytics teams with data discovery, lineage, data quality, and collaboration capabilities across a modern data stack — with native integrations for Snowflake, BigQuery, Redshift, Databricks, dbt, Airflow, Kafka, and Tableau, designed as an open alternative to commercial data catalogs like Collibra, Alation, and Atlan for APAC enterprise teams.
OpenMetadata's data catalog — where all APAC data assets (tables, dashboards, pipelines, ML models, storage containers) are automatically ingested and classified with schema details, sample data, usage statistics, and data profiling metrics — enables APAC data consumers to discover trusted data assets through full-text search and faceted browsing without asking data engineers which table to use, reducing the 'which table do I query?' toil that consumes APAC analytics team time.
OpenMetadata's dbt and Airflow integration — where dbt model lineage, documentation, and test results are automatically synced to OpenMetadata, and Airflow DAG lineage is captured end-to-end — enables APAC data engineering teams to use OpenMetadata as the single source of truth for data pipeline documentation, combining dbt's transformation-level lineage with Airflow's orchestration-level lineage into a unified APAC data lineage graph.
OpenMetadata's data quality framework — where APAC data engineers define column-level tests (completeness, uniqueness, value range, custom SQL) through OpenMetadata's UI or YAML configuration, and test results are tracked historically with alerts on failures — enables APAC data teams to implement data quality monitoring without building custom testing infrastructure, with quality scores surfaced on each catalogued APAC table.
OpenMetadata's collaboration features — where APAC data consumers can request data access, add reviews and announcements to data assets, create data product definitions, and follow datasets for change notifications — enables APAC data teams to build a self-service data culture where business users can find, understand, and request access to APAC data assets without email-based data discovery workflows.
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