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Apache Hudi vs Datastrato Iceberg Lakehouse Platform

Apache Hudi

hudi.apache.org

Datastrato Iceberg Lakehouse Platform

datastrato.ai

Side by side

FigureApache HudiDatastrato Iceberg Lakehouse Platform
Price fromFree—
Free planYes—
Free trial—Yes
Open source—Yes
LinuxYesYes
API—Yes
Self-hostedYesYes
Plans published11
Spec score · Data Lakehouse Platforms8.0 (#6)8.4 (#4)
Founded2016LinkedIn lists Datastrato's founding year as 2023.
IntegrationsThe site lists integrations including Apache Spark, Apache Flink, Kafka, Debezium, Amazon S3, Google Cloud Storage, Azure Blob Storage, Trino, and dbt.The product page names Spark, Flink, Trino, and Dremio as Iceberg catalog clients, and says the same namespace also resolves across BigQuery.
SupportThe site points users to community channels including Slack, GitHub, and the Hudi mailing list for community participation and technical help.Standard and Premium support include a dedicated Slack Connect channel, named technical account manager and one-hour P0 response, with 24/7 response on Premium.
What it doesApache Hudi is an open data lakehouse platform that brings database functionality to data lakes and supports incremental processing for low-latency analytics.Datastrato provides a federated metadata catalog and Iceberg REST platform for governing data and AI assets across clouds, engines and formats.

Plans

Apache Hudi

  • Apache HudiFree

Apache Hudi pricing →

Datastrato Iceberg Lakehouse Platform

  • Datastrato EnterprisePriced on request

Datastrato Iceberg Lakehouse Platform pricing →

In their own words

Apache Hudi

Apache Hudi is a free, open-source data lakehouse platform that adds database capabilities to data lakes and supports incremental processing for low-latency analytics. It can update and delete records, with pluggable indexing for change-data-capture and streaming workloads. Transaction features include atomic writes, snapshot isolation, and non-blocking concurrency controls. Users can query historical table versions, roll back changes, and review commit history. Automated table services handle clustering, compaction, cleaning, file sizing, and indexing, while schema evolution and enforcement accommodate changing data. Listed integrations include Apache Spark, Apache Flink, Kafka, Debezium, Amazon S3, Google Cloud Storage, Azure Blob Storage, Trino, and dbt. Some integrations are read-only, so Spark or Flink may write Hudi tables for those systems to query. Downloads include source releases and Maven bundles, with PGP verification advised. Hudi relies on the security posture of its compute and storage environment.

Visit hudi.apache.org

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.

Visit datastrato.ai