AetherLake vs Datastrato Iceberg Lakehouse Platform

AetherLake is a Kubernetes-native data lakehouse that brings storage, catalog, federated SQL, streaming, orchestration, BI, and identity into a web control panel. Its stack includes MinIO, Trino, Apache Polaris, Kafka, Flink, dbt, Airflow, Superset, Spark, Milvus, Prometheus, Grafana, PostgreSQL, and Keycloak. The panel shows pod health and resource use, supports service restarts, and provides workspaces for dbt, Kafka, Flink SQL, Trino queries, and Iceberg catalogs. Kafka and Flink are enabled by default; project examples describe streaming Kafka data into Iceberg tables and querying topics through Trino. Keycloak supplies OIDC single sign-on across services, with data-admin, data-scientist, and data-engineer roles. Deployment prerequisites include Kubernetes, Helm 3.12 or later, kubectl, Docker, and an NGINX ingress controller. Deployment materials cover AWS, Azure, and Google Cloud. An MCP server gives AI assistants access to platform status, logs and restarts, Trino queries, Polaris catalogs, and Airflow DAGs. The control panel is bilingual in English and Turkish. Internal, evaluation, development, testing, and non-commercial use is free; commercial use requires a separate license.

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.