Hi!

I hope you are doing well and pumped to kick off new data platform initiatives!

I have been silent for a couple of months, submerged in daily deliveries. Nonetheless, I explored and learned new components and ways of working, that I'll be happy to share my findings with you over the next couple of weeks/emails.

Some of you missed my mastermind sessions - here's an update:
Mastermind #3 session about Lakehouse on Azure Data Platform is scheduled for Wednesday September 1st (14:00 UTC). Sign up here (let me know if you don't receive confirmation email).

Is Lakehouse mature enough to take over DWH workloads?

How do you approach Lakehouse implementation on Azure Data Platform?

Do you use Synapse, Databricks, Azure Data Lake Gen2, something else?

Let's share experiences and your findings!

Azure Synapse Serverless vs Databricks SQL Analytics

I've decided to compare Azure Synapse Serverless Pools to Databricks SQL Analytics - to see which technology is faster/cheaper as a query engine for my data lake data. 

• Compared runs for 1 GB, 10 GB (partitioned and non-partitioned) and 1 TB (partitioned and non-partitioned)
• Created dbt project to analyze log files, published on GitHub https://github.com/valdasm/databricks-synapse-benchmark
• Published dbt documentation (still early release, search for "agg" models) https://valdasm.github.io/databricks-synapse-benchmark/#!/overview
• Read more: https://www.dataplatformschool.com/blog/synapse-databricks-benchmark/

Reach out if you have any thoughts about the benchmark, and also about my dbt setup.

Valdas Maksimavičius

IT Architect & Microsoft Data Platform MVP

https://www.dataplatformschool.com 

Vilnius
Lithuania

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