Side by side
AetherLake vs Datastrato Iceberg Lakehouse Platform
Both stand on data lakehouse platforms. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
AetherLake brings a broad data stack and operational controls into a self-hosted Kubernetes platform. Its license distinguishes non-commercial use from commercial use, and production exposure calls for additional configuration.
Visit AetherLake
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
| AetherLake | Datastrato Iceberg Lakehouse Platform | |
|---|---|---|
| Free plan | Yes | Not published |
| Open source | Not published | Yes |
| Runs on | Self-hosted, Web | 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 | github.com | datastrato.ai |
| On data lakehouse platforms | #2 of 23 | #1 of 23 |
AetherLake: what it does well
- Kafka and Flink are enabled by default.
- The control panel includes SQL, catalog, and observability views.
- Keycloak provides OIDC single sign-on across services.
- Documented deployment materials cover AWS, Azure, and Google Cloud.
- The control panel supports English and Turkish.
What to know first
- Deployment requires Kubernetes and several other prerequisites.
- Commercial use requires a separate license.
- Production setup requires replacing placeholders and configuring secrets and TLS.
- Anonymous installation telemetry is enabled unless disabled.
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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