Azure Table Storage vs lakeFS

Azure Table Storage has no write-up on Specifiction yet; its figures are above.

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.