Think Different

  Let's dive into the evolution of Azure Databricks and its performance differences. Azure Databricks is a powerful analytics platform built on Apache Spark, designed to process large-scale data workloads. It provides a collaborative environment for data engineers, data scientists, and analysts. Over time, Databricks has undergone significant changes, impacting its performance and capabilities. Previous State: In the past, Databricks primarily relied on an open-source version of Apache Spark . While this version was versatile, it had limitations in terms of performance and scalability. Users could run Spark workloads, but there was room for improvement. Current State: Today, Azure Databricks has evolved significantly. Here’s what’s changed: Optimized Spark Engine: Databricks now offers an optimized version of Apache Spark . This enhanced engine provides 50 times increased performance compared to the open-source version. Users can leverage GPU-enabled clusters, enabling faster ...