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When comparing Databricks, AWS, Azure, and GCP (Google Cloud Platform), it’s essential to consider their strengths, use cases, and how they serve different types of organizations. Each platform offers robust cloud computing services, data analytics, machine learning, and storage solutions, but they have unique characteristics that make them suitable for different applications.
In this article we will break down the key differences among Databricks, Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). We will also highlight which platform might be better suited for specific use cases, including data engineering, machine learning, enterprise application integration, and multi-cloud strategies.
Overview of Each Platform
1. Databricks
Focus: Unified analytics platform primarily focused on big data processing and machine learning.
Core Offering: Built on Apache Spark, Databricks provides an environment for running Spark jobs, supporting big data analytics, and facilitating machine learning workflows.
Cloud Integration…
