ScaleOut Software

DECEMBER 10, 2019

Borrowed from its usage in product life-cycle management and simulation, a digital twin provides an object-oriented container for hosting application code and data. In the above power grid example, the application requires only of a few lines of code to embed a set of rules for interpreting state changes from a node in the power grid.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

Borrowed from its usage in product life-cycle management and simulation, a digital twin provides an object-oriented container for hosting application code and data. In the above power grid example, the code needed only consists of a few lines of Java code which embed a set of rules for interpreting state changes from a node in the power grid.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

APRIL 6, 2021

With the ScaleOut Digital Twin Streaming Service , an Azure-hosted cloud service, ScaleOut Software introduced breakthrough capabilities for streaming analytics using the real-time digital twin concept. Scaleout StreamServer® DT was created to meet this need.

IoT 52

IoT Azure Analytics Healthcare 52

ScaleOut Software

AUGUST 18, 2018

Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g., The higher-level digital twins continue to run in the cloud or on-premises – wherever the required computing resources are located.

IoT 40

IoT Ecommerce Analytics Latency 40

Alex Podelko

OCTOBER 3, 2017

It is only such vendor-neutral, 4-day, 5-track conference devoted completely to performance, capacity, scalability, and adjacent topics. The conference includes 80+ presentations on performance, capacity, cloud, IoT, security (and more) from best experts in these areas and several great panels. More information here.

IoT 113

IoT Performance Programming Performance Testing 113

ScaleOut Software

JULY 19, 2021

We are increasingly surrounded by intelligent IoT devices, which have become an essential part of our lives and an integral component of business and industrial infrastructures. Unlike manual or automatic log queries, in-memory computing can continuously run analytics code on all incoming data and instantly find issues.

IoT 78

IoT Analytics Big Data Architecture 78

The Netflix TechBlog

AUGUST 30, 2021

Complementing the hardware is the software on the RAE and in the cloud, and bridging the software on both ends is a bi-directional control plane. The challenge, then, is to be able to ingest and process these events in a scalable manner, i.e., scaling with the number of devices, which will be the focus of this blog post.

Latency 213

Latency Traffic Transportation Hardware 213

Enprowess

JANUARY 12, 2022

Internet of Things (IoT). Easy Deployment: PWAs can be deployed easily using a single code base that runs on accelerated mobile pages and web browsers. Internet of Things (IoT). IoT can be defined as a technology of interconnected devices where human involvement is not required for data transfer. How does IoT work?

Blockchain 59

Blockchain IoT Development Serverless 59

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. It then triggers application code to process the messages and gives it immediate access to memory-based contextual information for the data source. Sign up to use the service here.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. It then triggers application code to process the messages and gives it immediate access to memory-based contextual information for the data source. Sign up to use the service here.

Logistics 52

Logistics IoT Analytics Azure 52

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. To help ensure fast data access and scalability, IMDGs usually employ a straightforward key/value storage model.

Scalability 40

Scalability Cache Airlines Healthcare 40

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

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. To help ensure fast data access and scalability, IMDGs usually employ a straightforward key/value storage model.

Scalability 40

Scalability Cache Airlines Healthcare 40

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

ScaleOut Software

JANUARY 9, 2020

This dramatically simplifies application code and automatically scales its use by letting the execution platform run this code simultaneously for all stores. In addition, the cloud service hosts aggregate analytics that can continuously complete every few seconds, avoiding the need to wait for offline results from a data lake.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

This dramatically simplifies application code and automatically scales its use by letting the execution platform run this code simultaneously for all stores. In addition, the cloud service hosts aggregate analytics that can continuously complete every few seconds, avoiding the need to wait for offline results from a data lake.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

This dramatically simplifies application code and automatically scales its use by letting the execution platform run this code simultaneously for all stores. In addition, the cloud service hosts aggregate analytics that continuously run every few seconds, avoiding the need to wait for offline results from a data lake.

Logistics 52

Logistics Retail Analytics Azure 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

Apica

OCTOBER 29, 2019

including iPhones/ mobile devices, set-top boxes, game stations, and IoT devices. including iPhones/ mobile devices, set-top boxes, game stations, and IoT devices. DevOps Users should also be able to access code and or YAML style directly for advanced scripting, including full API support for all functions.

Performance Testing 40

Performance Testing Testing Performance Software 40

Apica

NOVEMBER 15, 2019

including iPhones/ mobile devices, set-top boxes, game stations, and IoT devices. Users should also be able to access code directly for advanced scripting, not only via the GUI. Cloud, on-premises, or hybrid –Users should be able to use the same test platform and scripts from the cloud, on-premises, or via a hybrid model.

Performance Testing 40

Performance Testing Testing Performance Games 40

All Things Distributed

DECEMBER 13, 2016

The British Government is also helping to drive innovation and has embraced a cloud-first policy for technology adoption. 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.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

APRIL 9, 2015

Once the models are created, you can get predictions for your application by using the simple API, without having to implement custom prediction generation code or manage any infrastructure. Amazon ML is highly scalable and can generate billions of predictions, and serve those predictions in real-time and at high throughput.

Lambda 122

Lambda Cloud IoT AWS 122

All Things Distributed

OCTOBER 7, 2015

QuickSight is a fast, cloud native, scalable, business intelligence service for the 1/10th the cost of old-guard BI solutions. QuickSight is a cloud-native BI service built from the ground up to address the big data challenges around speed, complexity, and cost. Big data challenges. Enter Amazon QuickSight.

Cloud 137

Cloud Big Data AWS Analytics 137

All Things Distributed

JULY 14, 2015

A more scalable option is to decouple these systems and build a pipe that connects these engines and feeds all change records from the source database to the data warehouse (e.g., However, in the past, you had to write code to manage the data changes and deal with keeping the search engine and data warehousing engines in sync.

Database 167

Database Lambda AWS IoT 167

All Things Distributed

JUNE 21, 2018

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

Database AWS Games Latency 167

Abhishek Tiwari

NOVEMBER 3, 2018

Although some vendors have added support for APIs and cloud services most have not even bothered to adapt with changing technology landscape. In addition, traditional CMS solutions lack integration with modern software stack, cloud services, and software delivery pipelines. There is hardly any innovation from traditional CMS vendors.

Systems 63

Systems Cache Website Network 63