Side by side
DataHub vs Datastrato Iceberg Lakehouse Platform
Both stand on active metadata management software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
DataHub combines metadata discovery, lineage, and observability, with a choice of self-hosted or managed deployment. Core is free to deploy; teams considering Cloud should account for use-based pricing and its managed support model.
Visit DataHub
Choose Datastrato if your team needs a federated Iceberg catalog with governance spanning data clients, storage, and agent access. Its enterprise deployment and on-request pricing make it a better fit for organizations prepared to evaluate and run a Kubernetes-based platform.
Visit Datastrato Iceberg Lakehouse PlatformThe facts
| DataHub | Datastrato Iceberg Lakehouse Platform | |
|---|---|---|
| Free plan | Yes | Not published |
| Open source | Yes | Yes |
| Runs on | API, Linux, Mac, Self-hosted, Web, Windows | API, Linux, Self-hosted |
| Lowest paid plan | Free or on request | Free or on request |
| Plans published | 2 | 1 |
| Maker | Not published | Not published |
| Website | datahub.com | datastrato.ai |
| On active metadata management software | #1 of 25 | #2 of 25 |
DataHub: what it does well
- Free, self-hosted Core option.
- Cloud includes more than 100 pre-built connectors.
- Column-level lineage spans sources and downstream assets.
- Cloud offers automated checks and anomaly detection.
- Cloud trial is advertised for 21 days.
What to know first
- Core requires users to manage installation and operations.
- Core lacks SSO and fine-grained permissions out of the box.
- Cloud pricing depends on data volume, users, and capabilities.
Datastrato Iceberg Lakehouse Platform: what it does well
- Registers multiple data sources in place without copying metadata.
- Supports Spark, Flink, Trino, Dremio, and BigQuery namespaces.
- Includes row filtering, column masking, and tag-based policies.
- Supports S3, GCS, and ADLS with scoped credentials.
- Maintenance jobs can be dispatched to Airflow, Kubernetes, EMR, or Databricks.
What to know first
- Enterprise pricing is available on request.
- Deployment requires a Kubernetes cluster and license key.
- Local evaluation also uses local Kubernetes.
- Audit reports and control documentation require NDA-gated access.
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