lakeFS vs Oracle Big Data Service

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.

Oracle Big Data Service is a managed cloud service for creating Hadoop-based data lakes that process large amounts of data. Its distribution includes Apache Hadoop, Ambari, HBase, Hive, Spark, and other services. Customers can build clusters with OCI compute shapes, from small development environments to large production clusters on dedicated hardware, and choose NVMe or block storage. Clusters can be resized; secure, high-availability clusters are an option. Oracle Cloud SQL queries data across Hadoop, Kafka, NoSQL, and object stores using Oracle SQL. The service also describes SparkR for working with HDFS, Spark DataFrames, and JDBC sources and building models in R. Access is available through the OCI Console, CLI, REST APIs, and SDKs. Block Volume data is encrypted at rest by default, and OCI IAM controls authentication and authorization. Oracle describes both short-lived clusters for specific tasks and long-running data lakes. The listed service fee is 0.02 USD per OCPU per hour; compute and storage charges apply separately. Oracle lists separate hourly rates for compute shapes and Cloud SQL. Clusters need release updates to remain current and supported.