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The Power of Integrated Analytics Within an IMDG

ScaleOut Software

For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache. Typical uses include storing session-state and ecommerce shopping carts, product descriptions, airline reservations, financial portfolios, news stories, online learning data, and many others.

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The Power of Integrated Analytics Within an IMDG

ScaleOut Software

For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache. Typical uses include storing session-state and ecommerce shopping carts, product descriptions, airline reservations, financial portfolios, news stories, online learning data, and many others.

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How To Choose A Headless CMS

Smashing Magazine

Working for a major airline not even a decade ago, I can remember trying to model content for mobile devices (yes! From a developer perspective, not only static assets need to be cached on a CDN. Many headless CMSes cache content retrieved via RESTful or GraphQL APIs. Look out for: Caching of images and content via CDN.

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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. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

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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. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

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Using Parallel Query with Amazon Aurora for MySQL

Percona

I will compare AWS Aurora with MySQL (Percona Server) 5.6 Aurora Parallel Query response time (for queries which can not use indexes) can be 5x-10x better compared to the non-parallel fully cached operations. 84.1 | | version_comment | Percona Server (GPL), Release 84.1, MySQL on ec2.

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