22-25 April 2026
SQLBits 2020

The Azure Spark Showdown - Databricks VS Synapse Analytics

Azure now has two slick, platform-as-a-service spark offerings, but which one should you choose? A separate specialist tools or a one-size-fits-all solution? Join Simon as he compares and contrasts the spark offerings.

We now have two slick, platform-as-a-service spark offerings in Azure, but which one should you choose? Azure Databricks is powering forward with advancements to the spark engine, a mature workspace and cross-platform compatibility, but Azure Synapse Analytics' new Spark engine sits at the beating heart of a fully integrated platform.

Which do you choose - separate specialist tools or a one-size-fits-all solution?

In this theory-based session we'll take a look at the key differences of the two spark engines, contrasting them on power, cost and functionality. By the end of the session, you will be equipped with all the knowledge to pick the right solution for you going forward. Given the scope of the two platforms, we'll be sticking at high level comparisons rather than code demonstrations.

Speakers

Simon Whiteley

advancinganalytics.co.uk/blog

Simon Whiteley's previous sessions

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This session session aims to give you that context. We'll look at how spark-based engines work and how we can use them within Synapse Analytics. We'll dig into Delta, the underlying file format that enables the Lakehouse, and take a tour of how the Synapse compute engines interact with it. Finally, we'll draw out our whole Lakehouse architecture
 
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Databricks, Lakes & Parquet are a match made in heaven, but explode with extra power when using Delta Lake. This session will dive into the details of how Databricks Delta works and how to make the most of it.
 
The Azure Spark Showdown - Databricks VS Synapse Analytics
Azure now has two slick, platform-as-a-service spark offerings, but which one should you choose? A separate specialist tools or a one-size-fits-all solution? Join Simon as he compares and contrasts the spark offerings.
 
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