AtScale Blog

Trystan here, Software Engineer and doer of all things technical at AtScale.  Which SQL-on-Hadoop engine performs best?  We get this question all the time!

We looked around and found that no one had done a complete and impartial benchmark test of real-life workloads across multiple SQL-on-Hadoop engines (Impala, Spark, Hive...etc).

So, we decided to put our enterprise experience to work and deliver the world's first BI-on-Hadoop performance benchmark.  

What did we find out?  Well, turns out that the right question to ask is: "Which engine performs best for Which query type?".  We looked across three of the most common types of BI queries and found that each engine had a particular niche.  Bottom line: One Engine does NOT fit all.

Read on to find out the details of our environment and configuration, the types of queries we tested... (or download the full whitepaper here)

Every once in awhile, our team gets questions about the validity of Hadoop.  Why it exists, why people should consider using it, etc.   In the below video, I provide a few examples of cases across common industries like financial services or retail that provide a clear answer to this question.  

As usual, the video lasts less than 2 minutes so don't expect to have to sit through long, esoteric explanations.  We get to the point and very quickly at AtScale!  

If your team has been trying to connect your Business Intelligence (BI) tools to your Hadoop environment, you're familiar with the typical issues: performance, security and the inability to model the data in a way that business users like to consume it.