Remove Cache Remove Ecommerce Remove IoT Remove Performance
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The Amazing Evolution of In-Memory Computing

ScaleOut Software

From Distributed Caches to Real-Time Digital Twins. Going back to the mid-1990s, online systems have seen relentless, explosive growth in usage, driven by ecommerce, mobile applications, and more recently, IoT.

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The Amazing Evolution of In-Memory Computing

ScaleOut Software

From Distributed Caches to Real-Time Digital Twins. Going back to the mid-1990s, online systems have seen relentless, explosive growth in usage, driven by ecommerce, mobile applications, and more recently, IoT.

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Top 9 web development trends to expect in 2022

Enprowess

Internet of Things (IoT). So it is convenient for all to use irrespective of internet speed and it works offline using cached data. Consistent with the Statista report, 9% of eCommerce firms invested in progressive web apps (PWA) in 2021. Internet of Things (IoT). How does IoT work? IoT tracking systems.

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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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A one size fits all database doesn't fit anyone

All Things Distributed

As I have talked about before, one of the reasons why we built Amazon DynamoDB was that Amazon was pushing the limits of what was a leading commercial database at the time and we were unable to sustain the availability, scalability, and performance needs that our growing Amazon.com business demanded. The opposite is true.

Database 167