Is Databricks Open Source


        Is Databricks Open Source

Databricks isn’t entirely open source. Here’s a breakdown of what is and isn’t:

Core Components (Open Source)

  • Apache Spark: The core computational engine of Databricks is based on the open-source Apache Spark project.
  • Delta Lake: An open-source storage layer that brings reliability and performance improvements to data lakes.
  • MLflow: An open-source platform for managing the end-to-end machine learning lifecycle.

Proprietary Components (Not Open Source)

  • Databricks Platform: The cloud-based platform itself, which includes features like:
    • Managed clusters
    • Collaborative notebooks
    • Integrated job scheduling
    • Security and governance tools
    • Unity Catalog (for data governance and lineage)
  • Databricks Runtime: A curated and optimized version of Apache Spark with additional libraries and performance enhancements.

Why this model?

  • Innovation: The proprietary components allow Databricks to provide features and optimizations not readily available in the core open-source projects.
  • Ease of Use: The managed platform simplifies setup, deployment, and maintenance for users, especially in cloud environments.
  • Commercial Sustainability: The commercial side supports the funding and development of the open-source projects Databricks contributes to.

In Summary:

Databricks leverages the power of open source while offering a value-added platform with enhanced features and a focus on user experience.

Databricks Training Demo Day 1 Video:

You can find more information about Databricks Training in this Dtabricks Docs Link



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