How to Escape the MPP Database Schema Management Hell
Tuesday, March 10, 2015
Today’s massively parallel processing (MPP) databases’ ability to run large-scale analytic queries very quickly make them great tools for iterative data exploration. And Cloud offerings like Redshift are causing MPP databases to enjoy increasing adoption outside of enterprise IT.
However, schema management and data loading are two areas where MPP databases require an enormous amount of technical expertise and engineering manpower. There are ways to mitigate this problem with solutions offered by companies like Treasure Data, a company that offers a cloud service for the entire data pipeline, including acquisition, storage, and analysis.
Using Treasure Data alongside MPP databases can significantly lessen the impact of these types of issues. To explain how, Treasure Data’s Kiyoto Tamura has published an article explaining how migrating from a “Redshift only” setup to “Treasure Data + Redshift” setup facilitates the elimination of schema management and data loading challenges.
You can check out Tamura’s full how-to article on the Treasure Data website.
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