Databricks is a unified analytics platform that combines the power of Apache Spark, Delta Lake, and MLFlow with cloud-native infrastructure-a One-Stop Shop-to simplify the end-to-end analytics process. Its origins trace back to the University of California, Berkeley, where its creators developed tools such as Apache Spark, Delta Lake and MlFlow. Let's see how these two data titans stack up! Snowflake vs Databricks-Comparing the Cloud Data Titans What is Databricks?ĭatabricks-The Data Lakehouse Pioneer-is a cloud-based data lakehouse platform founded in 2013 that today offers a unified analytics platform for data and AI. In this article, we will compare Snowflake vs Databricks (❄️ vs □) across 5 different key criteria-architecture, performance, integration/ecosystem, security, machine learning capabilities and more!! We'll highlight the unique capabilities and use cases of each platform, and outline the core pros and cons to consider. Databricks, on the other hand, began as a cloud service for Apache Spark, aiming to be a one-stop shop for data engineering, analytics, and machine learning capabilities. So, which platform comes out on top? Snowflake has established itself as a best-in-class cloud data warehouse, providing instant elasticity and separation of storage and compute. Both of ‘em aim to simplify working with data in the cloud, but they go about it in very different ways. Snowflake and Databricks are two leading cloud data platforms.
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