ScaleOut Software

JUNE 22, 2020

Going back to the mid-1990s, online systems have seen relentless, explosive growth in usage, driven by ecommerce, mobile applications, and more recently, IoT. From Distributed Caches to Real-Time Digital Twins. For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ScaleOut Software

JUNE 22, 2020

Going back to the mid-1990s, online systems have seen relentless, explosive growth in usage, driven by ecommerce, mobile applications, and more recently, IoT. From Distributed Caches to Real-Time Digital Twins. For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time. The list goes on.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time. The list goes on.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JULY 14, 2021

The population of intelligent IoT devices is exploding, and they are generating more telemetry than ever. The Microsoft Azure IoT ecosystem offers a rich set of capabilities for processing IoT telemetry, from its arrival in the cloud through its storage in databases and data lakes.

IoT 52

IoT Azure Analytics Serverless 52

ScaleOut Software

JANUARY 9, 2020

In addition, real-time information on sales and inventory gives managers new tools that help optimize overall performance and maximize profits. To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

In addition, real-time information on sales and inventory gives managers new tools that help optimize overall performance and maximize profits. To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

In addition, real-time information on sales and inventory gives managers new tools that help optimize overall performance and maximize profits. To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

SEPTEMBER 20, 2018

This model organizes key information about each data source (for example, an IoT device, e-commerce shopper, or medical patient) in a software component that tracks the data source’s evolving state and encapsulates algorithms, such as predictive analytics, for interpreting that state and generating real-time feedback.

Programming 63

Programming IoT Java Analytics 63

ScaleOut Software

SEPTEMBER 20, 2018

This model organizes key information about each data source (for example, an IoT device, e-commerce shopper, or medical patient) in a software component that tracks the data source’s evolving state and encapsulates algorithms, such as predictive analytics, for interpreting that state and generating real-time feedback.

Programming 40

Programming IoT Java Analytics 40

All Things Distributed

JULY 14, 2015

In this blog post, I will explain how these three new capabilities empower you to build applications with distributed systems architecture and create responsive, reliable, and high-performance applications using DynamoDB that work at any scale. Amazon Redshift) and Elasticsearch machines. DynamoDB Cross-region Replication.

Database 167

Database Lambda AWS IoT 167

All Things Distributed

DECEMBER 13, 2016

The council has deployed IoT Weather Stations in Schools across the City and is using the sensor information collated in a Data Lake to gain insights on whether the weather or pollution plays a part in learning outcomes. Real-time monitoring and evaluation of events have led to a positive impact on performance or operations.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

APRIL 9, 2015

Amazon ML is highly scalable and can generate billions of predictions, and serve those predictions in real-time and at high throughput. When we designed Amazon EFS we decided to build along the AWS principles: Elastic, scalable, highly available, consistent performance, secure, and cost-effective. Amazon Lambda.

Lambda 122

Lambda Cloud IoT AWS 122

ScaleOut Software

JULY 27, 2018

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.

Scalability 40

Scalability Cache Airlines Healthcare 40

ScaleOut Software

JULY 27, 2018

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.

Scalability 40

Scalability Cache Airlines Healthcare 40

ScaleOut Software

MAY 19, 2020

This highly scalable cloud service is designed to simultaneously and cost-effectively track telemetry from millions of data sources and provide real-time feedback in milliseconds while simultaneously performing continuous, aggregate analytics every few seconds.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

MAY 19, 2020

This highly scalable cloud service is designed to simultaneously and cost-effectively track telemetry from millions of data sources and provide real-time feedback in milliseconds while simultaneously performing continuous, aggregate analytics every few seconds.

Logistics 52

Logistics IoT Analytics Azure 52

Enprowess

SEPTEMBER 7, 2021

JavaScript is one of the most famous and loved programming languages nowadays. It is growing day by day and has kept its position for eight years in a row and belongs to the top ten most loved programming languages. IoT-based applications. Enhanced performance: It has an Asynchronous or Non-blocking nature.

Open Source 52

Open Source Virtualization Programming Servers 52

ScaleOut Software

MAY 4, 2018

For example, if an IoT application is attempting to detect whether data from a temperature sensor is predicting the failure of the medical freezer to which it is attached, it looks at patterns in the temperature changes, such as sudden spikes or a continuously upward trend, without regard to the freezer’s usage or service history.

Processing 40

Processing IoT Programming Software Engineering 40

ScaleOut Software

MAY 4, 2018

For example, if an IoT application is attempting to detect whether data from a temperature sensor is predicting the failure of the medical freezer to which it is attached, it looks at patterns in the temperature changes, such as sudden spikes or a continuously upward trend, without regard to the freezer’s usage or service history.

Processing 40

Processing IoT Programming Software Engineering 40

ScaleOut Software

DECEMBER 10, 2019

For these reasons, most streaming applications only perform rudimentary analysis (often in the form of queries) on the incoming data stream and push most of the event messages into a data lake for offline examination. Note that the platform can seamlessly scale its performance by running thousands of real-time digital twins in parallel.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

For these reasons, most streaming applications only perform rudimentary analysis (often in the form of queries) on the incoming data stream and push most of the event messages into a data lake for offline examination. Note that the platform can seamlessly scale its performance by running thousands of real-time digital twins in parallel.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

For these reasons, most streaming applications only perform rudimentary analysis (often in the form of queries) on the incoming data stream and push most of the event messages into a data lake for offline examination. Note that the platform can seamlessly scale its performance by running thousands of real-time digital twins in parallel.

Code 52

Code Analytics Healthcare IoT 52