Datastrato Iceberg Lakehouse Platform vs Zeenea Data Discovery Platform
Datastrato Iceberg Lakehouse Platform
datastrato.aiZeenea Data Discovery Platform
actian.comSide by side
| Figure | Datastrato Iceberg Lakehouse Platform | Zeenea Data Discovery Platform |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | Yes | — |
| Open source | Yes | — |
| Web | — | Yes |
| Windows | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | — |
| Plans published | 1 | 2 |
| Spec score · Active Metadata Management Software | 8.3 (#6) | 7.1 (#16) |
| Deployment | Datastrato Enterprise is installed from a Helm chart into a Kubernetes cluster and activated with a license key; local evaluation uses local Kubernetes. | The current platform page describes cloud-native deployment across multi-cloud, hybrid, and on-premises environments. |
| Founded | LinkedIn lists Datastrato's founding year as 2023. | 2017 |
| Purpose | Datastrato is a federated metadata catalog built on Apache Gravitino and Iceberg REST Catalog for connecting data sources and governing access across clients. | The platform helps organizations discover, govern, and use data through catalog, metadata management, lineage, governance, and marketplace capabilities. |
Plans
Datastrato Iceberg Lakehouse Platform
- Datastrato EnterprisePriced on request
Zeenea Data Discovery Platform
- Basic data discoveryPriced on request
- Custom data discoveryPriced on request
In their own words
Datastrato Iceberg Lakehouse Platform
Datastrato Iceberg Lakehouse Platform is a federated metadata catalog for connecting data sources and governing access across clients. Built on Apache Gravitino and Iceberg REST Catalog, it provides a standards-compliant REST catalog with metadata caching and table maintenance for production lakehouses. It can register Iceberg, Hive, Glue, relational databases, Kafka, filesets, and models in place without copying metadata. Spark, Flink, Trino, and Dremio are named Iceberg catalog clients, and the same namespace resolves across BigQuery. Governance includes catalog-level role-based access, row filtering, column masking, tag-based policies, and auditing across engines and agents. S3, GCS, and ADLS are supported with short-lived scoped credentials per principal. Agents can use an MCP metadata interface and GVFS under the same access controls. Per-table compaction, snapshot expiry, and orphan cleanup jobs can be sent to Airflow, Kubernetes, EMR, or Databricks. Enterprise is installed with a Helm chart in Kubernetes and activated by license key. Pricing is on request; the commercial distribution includes support with a defined response commitment and maintained release line.
Zeenea Data Discovery Platform
Zeenea Data Discovery Platform has no write-up on Specifiction yet; its figures are above.