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intermix Blog

Best practices and lessons learned for cloud ETL and data engineering.

4 Real World Use Cases for Amazon Redshift

5 min READ
November 11th 2017
Since Amazon Redshift launched in 2013, customer keep asking us  "what are some of the uses cases for Amazon Redshift?". It's 2017, and with the four years since launch, that's a long time in technology. Key things that have changed since then:new Amazon Redshift features: more to do with […]
Lars Kamp Lars Kamp

World-class Data Engineering with Amazon Redshift - Training

1 min READ
October 26th 2017
Our training classes cover strategies and best practices for designing a data platform using Amazon Redshift. The concepts we cover focus on cluster stability, engineering productivity and query / dashboard speeds. The sessions have hands-on demos and individual coaching, arming you with the right tools […]
Nikola Sokolov Nikola Sokolov

Apache Spark vs. Amazon Redshift: Which is better for big data?

7 min READ
July 18th 2017
Every day, we talk to companies who are in the early phases of building our their data infrastructure.  A lot of times these conversations circle around which technology to pick for which job. For example, we often get the question "what's better - Spark or Amazon Redshift?", or "which one should w […]
Lars Kamp Lars Kamp

3 Things to Avoid When Setting Up an Amazon Redshift Cluster

4 min READ
February 2nd 2016
Amazon Redshift is a petabyte-scale data warehouse. Since its launch in 2012, it has seen huge adoption. It's easy to spin up a cluster, pump in data and begin performing advanced analytics in under an hour. Products like Fivetran are very powerful in that context. Fivetran replicates data from business […]
Lars Kamp Lars Kamp
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