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 Iceberg 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. Its named catalog clients include Spark, Flink, Trino, and Dremio, and the same namespace also resolves across BigQuery. Governance features include catalog-level role-based access, row filtering, column masking, tag-based policies, and audit across engines and agents. The platform supports S3, GCS, and ADLS, with short-lived scoped credentials issued per principal. Agents can use an MCP metadata interface and GVFS for files under the same access and audit controls. Per-table compaction, snapshot expiry, and orphan cleanup jobs can be dispatched to Airflow, Kubernetes, EMR, or Databricks. Datastrato Enterprise is installed from a Helm chart into a Kubernetes cluster and activated with a license key; local evaluation uses local Kubernetes. The paid Enterprise plan is priced on request. The company states SOC 2 Type II, ISO 27001 readiness, HIPAA BAA, and GDPR alignment.
Who it is for
Datastrato describes the platform for enterprise teams and developers working on metadata management, governance, and AI-ready infrastructure. It may fit organizations that need to connect multiple data systems while applying shared access controls and catalog governance across clients and agents.
What is good
- 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.
- Enterprise includes support with a defined response commitment.
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.
Verdict
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.
Get started with Datastrato Iceberg Lakehouse Platform
- Contact Datastrato for Enterprise pricing.
- Prepare a Kubernetes cluster, or use local Kubernetes for evaluation.
- Install Datastrato Enterprise from its Helm chart.
- Activate the installation with a license key.
- Connect supported data sources and catalog clients.
Limits to know first
The listed Enterprise plan has pricing on request and requires deployment with a license key. Audit reports and control documentation require NDA-gated access.
Questions about Datastrato Iceberg Lakehouse Platform
How is Datastrato Enterprise priced?
Pricing is on request; the listed Enterprise plan does not state a price.
How is it deployed?
Datastrato Enterprise is installed from a Helm chart into Kubernetes and activated with a license key. Local evaluation uses local Kubernetes.
Which data sources can it register?
It can register Iceberg, Hive, Glue, relational databases, Kafka, filesets, and models in place.
Which clients and integrations are named?
The product page names Spark, Flink, Trino, and Dremio as Iceberg catalog clients. It also says the same namespace resolves across BigQuery.
Which cloud storage systems does it support?
It supports S3, GCS, and ADLS, with short-lived scoped credentials vended per principal.
What compliance and security details does Datastrato state?
Its homepage states SOC 2 Type II, ISO 27001 readiness, HIPAA BAA, and GDPR alignment. Audit reports and control documentation require NDA-gated access.
Datastrato Iceberg Lakehouse Platform plans and pricing
All plansCompared on data lakehouse platforms
- Storage model
- external
- SQL analytics
- Yes
- ACID transactions
- Yes
- Table format support
- open
- Streaming ingestion
- Yes
- Governance catalog
- Yes
