Amazon Redshift Performance – Bigger Clusters, or Bigger Nodes?

Last week, I looked into options for increasing the performance of an Amazon Redshift cluster that was currently using 10 large dense compute nodes (dc1.large). While investigating, I noticed that a cluster of 32 dc1.large nodes (the maximum for that node type) had the same number of CPUs, the same amount of storage, and a comparable amount of RAM to a cluster of 2 dc1.8xlarge nodes (the minimum for that node type), while offering significant cost savings for anything less than a 3-year term. This got me wondering... if you want a cluster that's around that size, which is a better bet for performance?

We'll get the answer out of the way early for the tl;dr crowd.

Redshift performance graph.

The results of testing out three diverse queries on various-sized Redshift clusters.

The cluster of 32 dc1.large nodes provided substantially (13%, on average) faster performance for all but the shortest query in my test batch. Given the superior performance and lower cost, it was the obvious choice for a cluster of this size. Whenever more performance is called for, it will make sense to switch to a cluster of 3 dc1.8xlarge nodes...

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