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Comparison between Snowflake and Databricks

Snowflake follows the traditional enterprise data warehouse; you canu2019t query data in Snowflake except by using the Snowflake query engine. Databricks promotes the data lakehouse paradigm but is also pointed in the same direction as Snowflake; you must use Delta Lake, and while Delta Lake is open core its utility is limited without Databricksu2019 proprietary enhancements.DatabricksBased on open core distribution model.<br><br>https://hkrtrainings.com/snowflake-vs-databricks

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Comparison between Snowflake and Databricks

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  1. Comparison between Snowflake and Databricks Snowflake follows the traditional enterprise data warehouse; you can’t query data in Snowflake except by using the Snowflake query engine. Databricks promotes the data lakehouse paradigm but is also pointed in the same direction as Snowflake; you must use Delta Lake, and while Delta Lake is open core its utility is limited without Databricks’ proprietary enhancements.DatabricksBased on open core distribution model. Reserves key features for its commercial products. The resulting “walled garden” creates vendor lock-in no different than a top-to-bottom proprietary stack.Requires a specialized skill set to manage and maintain infrastructure. For example, demands experience fine-tuning Spark, which in turn calls for expertise in Scala, Python, and distributed systems.Relies on proprietary Delta Lake file format on top of a cloud object storage layer and SQL query engine to expand beyond the original data science use cases for which it had been known. SnowflakeCloud-based from its inception.Upon ingest, organizes data into the company’s proprietary columnar format, creating vendor lock-in.SQL-centric.Built on top of cloud infrastructure in AWS, GCP, and Azure. Recently added support for unstructured data to expand beyond the original BI and reporting use cases for which it had been known. For more info :-https://hkrtrainings.com/snowflake-vs-databricks

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