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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. Offloading the database boosts performance, reduces bottlenecks, and lowers costs. That’s where performance problems can begin.

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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. Offloading the database boosts performance, reduces bottlenecks, and lowers costs. That’s where performance problems can begin.

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Using Parallel Query with Amazon Aurora for MySQL

Percona

On multi-core machines – which is the majority of the hardware nowadays – and in the cloud, we have multiple cores available for use. I’m using the “Airlines On-Time Performance” database from [link] (You can find the scripts I used here: [link] ). With faster disks (i.e. AWS Aurora (based on MySQL 5.6) MySQL on ec2.

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