Datafold offers two solutions for data diffing: an open-source Python package called data-diff and a SaaS platform known as Datafold Cloud. Data diffing, akin to git code diffing but for database tables, involves comparing two tables to identify changes in value, schema, or row count. The open-source data-diff is ideal for individual developers or small teams needing ad hoc comparisons, particularly during development or data migrations, and integrates with dbt for enhanced model comparison. In contrast, Datafold Cloud is tailored for larger teams requiring automated data diffs, comprehensive column-level lineage for dependency analysis, and secure, compliant operation in environments like SOC 2, HIPAA, and GDPR. It supports a variety of workflows, including CI-integrated diffing, offering detailed insights into how changes impact data ecosystems, including BI tools and data apps. The best choice between the two depends on team size, data complexity, need for automation, and compliance requirements.