Azure Synapse vs Databricks: Choosing the Right Big Data Platform

In the rapidly evolving landscape of big data analytics, organizations are faced with the challenge of selecting the right platform that aligns with their data processing needs.

Two prominent contenders in this space are Azure Synapse and Databricks. In this article, we will delve into a comprehensive comparison of these platforms.

What is Azure Synapse?

1. Azure Synapse Analytics, SQL Data Warehouse a Microsoft’s integrated analytics service.
2. It bridges the gap between data warehousing and big data analytics.
3. Azure Synapse allows to analysis of vast amounts of data in real time.
4. Azure Synapse provides unified and real-time analytics, offers integration with ADLs, PowerBI, and other services of Microsoft, and based on the workload can up or down resources(scalability).

What is Databricks:

1. Databricks powered by Apache Spark is a cloud-based, open, and collaborative environment for data engineering, data science, and machine learning.
2. It offers a unified analytics platform, and collaborative workspace for data engineering, data science, and machine learning.
3. Includes machine learning capabilities and based on the workload can up or down resources(scalability).

Azure Synapse vs Databricks:

1. Synapse has an open-source Spark version with built-in support for .NET, whereas Databricks has an optimized version of Spark which offers increased performance and this allows users to select GPU-enabled clusters that will process data faster and have a higher data concurrency.
2. Synapse successfully integrates analytical services to bring enterprise data warehouse and big data analytics into a single platform, whereas, on the other hand, Databricks not only does big data analytics but also allows users to build complex ML products.
3. Databricks uses a group of magic commands which are known as DBUtils but Microsoft has invested time into Synapse to bring out the equivalent known as MSSparkUtils.