Delta Lake

    Who this is for:

    Architecture / Concept Overview: Delta Lake

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    *Delta Lake powers the medallion architecture, providing reliability guarantees at every layer from raw ingestion through curated analytics.*

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    *Core capabilities of Delta Lake that together deliver a reliable, performant lakehouse storage layer.*

    Key Terms

    Prerequisites and Setup

    • A Databricks workspace on AWS, Azure, or GCP with Unity Catalog enabled
    • A cluster running Databricks Runtime 13.3 LTS or later (Delta Lake is included)
    • Basic familiarity with PySpark DataFrames and Spark SQL
    • CREATE TABLE and MODIFY permissions on the target catalog and schema

    Step-by-Step Implementation

      Configuration Reference

      Delta Lake configuration options
      PropertyDefaultDescription
      delta.enableChangeDataFeedfalseEnables Change Data Feed for downstream CDC consumers
      delta.logRetentionDuration30 daysHow long commit history is preserved
      delta.deletedFileRetentionDuration7 daysMinimum age of files eligible for VACUUM
      delta.autoOptimize.optimizeWritetrueCoalesces small files on write
      delta.autoOptimize.autoCompacttrueTriggers background compaction after writes
      delta.tuneFileSizesForRewritestrueAdjusts target file size during OPTIMIZE
      delta.enableDeletionVectorstrueMarks rows as deleted without rewriting files

      Monitoring, Cost, and Security Considerations

      Common Pitfalls and Recommended Patterns

        Frequently Asked Questions