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Databricks: Difference between revisions
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The '''Databricks''' platform is a unified, cloud-based solution that empowers organizations to manage and analyze vast amounts of data while integrating advanced artificial intelligence (AI) capabilities, built upon the open-source Apache Spark framework. Founded in 2013 by the creators of Spark at UC Berkeley’s AMPLab, it combines the strengths of data lakes and data warehouses into a "lakehouse" architecture, supporting data engineering, data science, and machine learning workloads. Notable for its scalability and collaborative tools, Databricks serves over 10,000 organizations globally, including major corporations like Comcast and Shell, and continues to evolve with innovations like Delta Lake and generative AI integrations. | The '''Databricks''' platform is a unified, cloud-based solution that empowers organizations to manage and analyze vast amounts of data while integrating advanced artificial intelligence (AI) capabilities, built upon the open-source Apache Spark framework. Founded in 2013 by the creators of Spark at UC Berkeley’s AMPLab, it combines the strengths of data lakes and data warehouses into a "lakehouse" architecture, supporting data engineering, data science, and machine learning workloads. Notable for its scalability and collaborative tools, Databricks serves over 10,000 organizations globally, including major corporations like Comcast and Shell, and continues to evolve with innovations like Delta Lake and generative AI integrations. | ||
{{ | {{<span class="error">Expansion depth limit exceeded</span>|url=https://www.databricks.com}} | ||
==Goals== | ==Goals== | ||
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==References== | ==References== | ||
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[[Category:Programs and initiatives]] | [[Category:Programs and initiatives]] | ||