What is the difference between Amazon Redshift and Amazon Redshift Spectrum and Amazon Aurora?

byYaara Gazit
Updated Jul 3, 2017

Amazon Aurora is a relational database engine. It’s designed to be compatible with MySQL 5.6, so that existing MySQL applications and tools can run without requiring modification. It’s good for production usage for lots of applications but not necessarily for complex data analytics.

Amazon Redshift is a fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. It allows you to run complex analytic queries, but as fast as it is, it is not suited for production applications.

Amazon Simple Storage Service (Amazon S3) is a service for storing objects, and Amazon Redshift Spectrum enables you to run Amazon Redshift SQL queries against exabytes of data in Amazon S3. By using it, you can extend the analytic power of Amazon Redshift beyond data stored on local disks in your data warehouse to query vast amounts of unstructured data in your Amazon S3 “data lake” -- without having to load or transform any data. Basically, Amazon Redshift Spectrum is a new extension of Amazon Redshift, allowing you to save money on classic Redshift storage.

I know these services pretty well from my job as an engineer at Alooma, where we help companies build their data pipelines which process and migrate data from relational DB’s like Amazon Aurora to data warehouses like Amazon Redshift.

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