Datastrato Iceberg Lakehouse Platform vs Onehouse Cloud
Datastrato Iceberg Lakehouse Platform
datastrato.aiOnehouse Cloud
onehouse.aiSide by side
| Figure | Datastrato Iceberg Lakehouse Platform | Onehouse Cloud |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | Yes | Yes |
| Open source | Yes | — |
| Web | — | Yes |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | — |
| Plans published | 1 | 1 |
| Spec score · Data Lakehouse Platforms | 8.4 (#4) | 7.4 (#12) |
| Founded | LinkedIn lists Datastrato's founding year as 2023. | 2021 |
| Purpose | Datastrato is a federated metadata catalog built on Apache Gravitino and Iceberg REST Catalog for connecting data sources and governing access across clients. | Onehouse is a fully managed lakehouse platform for analytics and AI that runs in the customer's VPC. |
Plans
Datastrato Iceberg Lakehouse Platform
- Datastrato EnterprisePriced 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.
Onehouse Cloud
Onehouse Cloud is a managed lakehouse platform for analytics and AI that operates in a customer's virtual private cloud. It combines ingestion, compute, table services, query engines, and catalog synchronization for cloud-storage data. OneFlow incrementally writes Apache Hudi, Apache Iceberg, and Delta Lake tables. Quanton runs SQL, Spark jobs, and PySpark notebooks with autoscaling compute. Managed open-engine clusters support Trino, Apache Flink, and Ray. Automated table services are intended to improve query speed, with Onehouse stating results can be up to 10 times faster on tables. OneSync synchronizes metadata with Snowflake, Databricks Unity Catalog, Google Data Catalog, and AWS Glue. Onehouse says data remains in the customer's account and VPC, encrypted at rest and in motion. Project-level roles, audit logs, SOC 2 Type 1 and 2 certification, and PCI DSS compliance are listed. Usage-based billing uses Onehouse Compute Units, while cloud infrastructure is paid separately. A 30-day OneFlow trial includes $1,000 credit.