Cloudera Data Lake Service vs lakeFS

Cloudera Data Lake Service provides data governance, metadata management, access controls, and auditing for data lake workloads. It captures schema and metadata definitions that platform workloads discover or create, then supports search, lineage, chain-of-custody auditing, classification, profiling, and a business glossary. Security capabilities include role- and attribute-based policies, auditing of unauthorized access, and encryption at rest and in motion with key management. Apache Ranger can apply access policies at database, table, column, and file levels, including dynamic conditions such as time or geolocation. Apache Knox provides a protected single sign-on gateway to Data Lake and Cloudera Data Platform interfaces. A cluster includes Hive Metastore, Ranger, Atlas, and Knox. Cloudera supports light-duty and enterprise Data Lakes on AWS, Azure, and GCP. Listed capabilities also include SQL analytics, streaming ingestion, data sharing, and open table formats. The service has web and API access and supports hybrid deployment. The listed pricing note starts at $0.20, while the plan is also described as Contact Sales for pricing; cloud prices exclude infrastructure and networking costs.

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.