Datastrato Iceberg Lakehouse Platform vs OpenLake

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.

OpenLake is a managed data lakehouse platform deployed in a customer’s cloud account, with API, self-hosted, and web access. It combines Trino, Apache Spark, Apache Iceberg, Apache Polaris, Apache Superset, PostgreSQL, Neo4j, Elasticsearch, and Polars. Its browser SQL workbench uses Trino and can draft queries from natural-language prompts grounded in readable catalogs. Teams can schedule and monitor ETL jobs written in Spark, Polars, Python, or Bash, including work on temporary Spark clusters. Analysts can launch preconfigured cloud workstations through a browser or native client over a secure tunnel without public exposure. OpenLake connects Tableau, Power BI, databases, APIs, S3 feeds, and files. It describes SSO with enforced MFA, role-based permissions, managed secrets, network isolation, and audit logs. Deployments can use customer-owned buckets, open Iceberg tables, streaming ingestion, governance catalogs, and offline artifacts in networks without internet egress. AI cataloging, natural-language querying, and incident-triage proposals are included. Pricing is on request.