intermix Blog

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

Struggling with slow queries & locked tables? Here’s how to configure your Redshift cluster for performance

12 min READ
May 27th 2019
When customers start using intermix.io for the first time, they can see the set-up and configuration of their Amazon Redshift cluster in the context of their queries and workflows. At that point, customers experience one common reaction:“Knowing what we know now, how would we set up our Redshift cluster […]
Lars Kamp Lars Kamp

We Tested Amazon Redshift Concurrency Scaling: Here are our Results

4 min READ
April 3rd 2019
SummaryThe Amazon Redshift architecture allows to scale up by adding more nodes to a cluster. That can cause over-provisioning of nodes to address peak query volume. Unlike adding nodes, Concurrency Scaling adds more query processing power on an as-needed basis. The typical Concurrency Scaling […]
Stefan Gromoll Stefan Gromoll

How We Use AWS IAM to Generate Temporary Amazon Redshift Passwords

5 min READ
February 27th 2019
At intermix.io, we run a fleet of over ten Amazon Redshift clusters. In this post, I'll describe how we use AWS IAM authentication for our database users. By using IAM credentials, we can enforce security policies on users and passwords. It's a scalable and secure way to manage access to your cluster(s) […]
Christopher MacGown Christopher MacGown

AWS Redshift Architecture: Clusters & Nodes & Data Apps, oh my!

7 min READ
February 23rd 2019
In this post, we’ll lay out the 5 major components of Amazon Redshift’s architecture.Data applicationsClustersLeader nodesCompute nodesRedshift SpectrumUnderstanding the components and how they work is fundamental for building a data platform with Redshift. In the post, we’ll provide tips and refer […]
Lars Kamp Lars Kamp

Announcing Query Insights - Helping customers with growing data & query volume

3 min READ
January 28th 2019
The number one driver of change for our customers is that they are experiencing huge growth in data and query volume.We observe three main drivers behind that growth:Growth in the number of data sources connected to a Redshift cluster and the volume of data coming from those sources. We observe […]
Paul Lappas Paul Lappas
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