Data Engineering — Azure Databricks or Azure Synapse Analytics
The cloud is the fuel that powers today’s digital companies, with businesses paying solely for the specific services or resources that they consume over time.
Azure Synapse Analytics bridges the gap between these two worlds by providing a uniform experience for ingesting, preparing, managing, and serving data for instant BI and machine learning needs.
Databricks is ideal for the “processing” layer, whereas Azure Synapse Analytics is ideal for the serving layer due to access control, active directory integration, and interaction with other Microsoft products.
Azure Databricks and Azure Synapse Analytics are mostly used for machine learning, and Synapse is also a Data Warehouse, therefore it is optimised for OLAP.
Apache Spark powers both Databricks and Synapse Analytics. With optimized Apache Spark support, Databricks allows users to select GPU-enabled clusters that do faster data processing and have higher data concurrency.
Azure Synapse Analytics is an umbrella term for a variety of analytics solutions. It is a combination of Azure Data Factory, Azure Synapse SQL Pools (essentially what was formerly known as Azure SQL Data Warehouse), and some added capabilities such as serverless Spark clusters and Jupyter notebooks, all within a…
