DataHub Cloud vs OpenDataDiscovery Platform
DataHub Cloud
datahub.comOpenDataDiscovery Platform
opendatadiscovery.orgSide by side
| Figure | DataHub Cloud | OpenDataDiscovery Platform |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | Yes | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 1 |
| Spec score · Data Lineage Tools | 7.6 (#17) | 8.1 (#9) |
| Integrations | The connector directory lists more than 150 data and AI integrations, including BigQuery, Databricks, dbt, Snowflake, Tableau, and Airflow. | The product site lists integrations including MongoDB, ClickHouse, dbt, Snowflake, Tableau, BigQuery, Kafka, PostgreSQL, and others. |
| Purpose | DataHub Cloud automatically captures data lineage and shows downstream impact in real time. | OpenDataDiscovery describes itself as an end-to-end data discovery, observability, and governance platform. |
| Security | The security page says customer data is encrypted at rest and in transit, with AWS KMS used to manage encryption keys. | ODD supports authentication through LDAP, and its documentation warns against using its simple login-form authentication in production. |
| Support | The Cloud vs. Core page says DataHub Cloud customers receive onboarding, multi-team training, adoption support, a dedicated customer success team, and a private Slack support channel. | The product site lists a dedicated team, a helpful team, and a community as support options. |
Plans
In their own words
DataHub Cloud
DataHub Cloud has no write-up on Specifiction yet; its figures are above.
OpenDataDiscovery Platform
OpenDataDiscovery Platform is an open-source catalog for finding and governing data products across data teams. Search and facet filters help users locate metadata by source, owner, or tag, then explore ownership and related links. The platform traces data objects and microservices end to end, imports data quality test results, and shows dataset quality status. It also catalogs machine-learning experiment metadata and lineage and supports experiment logging, connecting data science and data engineering work. Teams can access collected metadata through a web interface or REST API, and deploy with Docker Compose, Kubernetes and Helm charts, or AWS Marketplace QuickLaunch. The catalog uses an open metadata collection standard to connect catalogs, tools, and feature stores; Lookup Tables support reference data governance. ODD supports LDAP authentication and USER and ADMIN roles. Its documentation cautions against simple login-form authentication in production. Metadata attachments are limited to 20 MB, while links can point to larger or remotely stored files. The platform is free and open source, with public development.