HPE Ezmeral Data Fabric vs lakeFS

HPE Ezmeral Data Fabric consolidates data from on-premises systems, multiple clouds and edge deployments into one logical store. It supports files, object data, NoSQL databases and streams, with transaction support, strong consistency, multi-region support and horizontal scaling. Application developers can use standard APIs, languages and protocols. Its object store provides S3 API access, WORM compliance, events delivered to data streams and compatibility with open-source AWS S3 and Minio SDKs. Analytics integrations include Apache Spark, Apache Drill, Presto and S3 Select, while certified open-source tools and engines can run directly on the fabric for in-place analytics. Security capabilities include FIPS 140-2 Level 1 support when FIPS mode is enabled and dynamic masking of designated fields in JSON queries. A community edition is available, and an enterprise 30-day trial license can be requested. The community edition has limited nodes, no high availability or technical support, lacks advanced storage options such as snapshots and global replication, and is not intended for production. Pricing is on request; as-a-service monthly charges depend on storage use and selected tier.

lakeFS provides data version control and governance for teams working with petabyte-scale multimodal data. Its engine records changes and uses branches, commits, merges, and rollbacks to manage data versions. Branches create isolated environments without copying data or adding storage costs. Write-Audit-Publish workflows use automated hooks and human review to check changes before merging. Immutable commits, tags, and lineage connect experiments and agent actions to the data versions behind them. Listed controls include role-based access, geo-based policies, data immutability, SSO, and SCIM; lakeFS states that it is SOC 2 compliant and provides audit trails and lineage. It works with AWS S3, Azure Blob, Google Cloud Storage, and on-premises object stores such as MinIO. Integrations include Spark, Trino, DuckDB, Databricks, MLflow, SageMaker, Vertex AI, Kubeflow, Airflow, and Airbyte. Enterprise can run as managed lakeFS Cloud or as a self-managed deployment on-premises, in a private cloud, or in an air-gapped environment. Pricing is on request, and a 15-day trial includes full Enterprise access and support from lakeFS experts.