Datastrato Iceberg Lakehouse Platform vs IOMETE

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.

IOMETE is a data lakehouse platform for AI and analytics built on Apache Spark, Apache Iceberg, and Kubernetes. It supports SQL analytics, ACID transactions, streaming ingestion, and open table formats, with external storage. Its Query Federation Engine can query relational and NoSQL databases and flat files without complex ETL pipelines. A centralized catalog holds dataset metadata, lineage, collaboration, and quality information. Teams can connect through JDBC/ODBC, REST APIs, SQL interfaces, custom endpoints, and webhooks. Integrations include Tableau, Power BI, and Apache Superset for business intelligence, as well as Apache Airflow, dbt, and Apache NiFi for data integration. Collaboration tools include a SQL editor, Git integration for SQL worksheets and queries, and multi-domain support. Access enforcement can operate at database, table, column, and row levels, with masking and row filters; authentication supports local credentials, LDAP synchronization, and federated SAML/OIDC. Deployment options include on-premises, private or public clouds, and hybrid environments. The Free plan allows up to 100 vCPUs and includes community support. Enterprise is listed at $500 per vCPU per year with a $100,000-per-year minimum commitment. Business Critical has a $250,000-per-year minimum commitment.