On a Comparison Map of Azure Databricks & Synapse

Azure declared rebranding of the Azure SQL Data Warehouse into Azure Synapse Analytics. But then, this was not a new name for the same service. Azure has added a lot of new functionalities to Azure Synapse to bridge the gap between big data and data warehousing technologies.

  • Synapse SQL
  • Provisioned Pool
  • On-demand Pool
  • Open-source Spark & Delta
  • Synapse Pipelines
  • Studio

When to use Azure Synapse Analytics and/or Azure Databricks?

Through the new functionalities in Synapse, we see some comparable functionalities as in Databricks, which raises how Synapse compares to Databricks and when to use which.

How Does Is Vary?

Recommendation Based on Specific Use-Cases

Machine Learning Development: In this case, the recommendation is to use Databricks, which has broader ML features within Spark and gives a more comfortable developer experience
Ad-Hoc Data Lake Discovery: In this case, the recommendation is to use the tool or UI you prefer. If you are a BI developer familiar with SQL & Synapse, Synapse is perfect; if you are a data scientist only using notebooks: use Databricks to discover your data lake.
Real-time transformations: In this case, the recommendation is to use Databricks if you want to use Spark’s Structured Streaming and load real-time data into your delta lake.
SQL Analyses & Data Warehousing: In this case, the recommendation is to use Synapse.
Reporting and Self-Service BI: In this case, the recommendation is to use Synapse. Use Power BI directly from Synapse Studio. The SQL pool (SQL DWH) is a leader in enterprise data warehousing.

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