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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. For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing.

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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. For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing.

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Expanding the Cloud – An AWS Region is coming to Hong Kong

All Things Distributed

After the launch of the AWS APAC (Hong Kong) Region, there will be 19 Availability Zones in Asia Pacific for customers to build flexible, scalable, secure, and highly available applications. In 2010, we opened our first AWS Region in Singapore and since then have opened additional regions: Japan, Australia, China, Korea, and India.

AWS 146
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Embrace event-driven computing: Amazon expands DynamoDB with streams, cross-region replication, and database triggers

All Things Distributed

I am excited to share with you that today we are expanding DynamoDB with streams, cross-region replication, and database triggers. Streams provide you with the underlying infrastructure to create new applications, such as continuously updated free-text search indexes, caches, or other creative extensions requiring up-to-date table changes.

Database 167
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A one size fits all database doesn't fit anyone

All Things Distributed

A common question that I get is why do we offer so many database products? To do this, they need to be able to use multiple databases and data models within the same application. Seldom can one database fit the needs of multiple distinct use cases. Seldom can one database fit the needs of multiple distinct use cases.

Database 167
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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.