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.

Analytics 52

Analytics IoT Lambda Big Data 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. This simplifies the installation process and ensures portability across operating systems.

IoT 52

IoT Azure Analytics Healthcare 52

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. Each of these categories opens up challenging problems in AI/visual algorithms, high-density computing, bandwidth/latency, distributed systems. cameras) in many usages ranging from digital security/surveillance and automated retail (e.g.

Wireless 54

Wireless IoT Analytics Architecture 54

Dynatrace

JUNE 1, 2021

Practitioners use APM to ensure system availability, optimize service performance and response times, and improve user experiences. Even a conflict with the operating system or the specific device being used to access the app can degrade an application’s performance. APM’s many forms.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

Adrian Cockcroft

FEBRUARY 13, 2023

Discussion of the water positive goal and optimizations that let AWS return water directly for irrigation rather than to the sewage system. SUS302 Optimizing architectures for sustainability — Katja Philipp AWS SA and Szymon Kochanski AWS SA. They optimized airflow in datacenters to reduce cooling energy use by 20%.

AWS 64

AWS Energy Architecture Programming 64

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. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

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. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

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

MAY 4, 2018

Traditional stream-processing and complex event processing systems, such as Apache Storm and Software AG’s Apama , have focused on extracting interesting patterns from incoming data with stateless applications. Michigan) in 2002 for use in product life cycle management, it was recently popularized for IoT by Gartner in a 2017 report.

Processing 40

Processing IoT Programming Software Engineering 40

ScaleOut Software

MAY 4, 2018

Traditional stream-processing and complex event processing systems, such as Apache Storm and Software AG’s Apama , have focused on extracting interesting patterns from incoming data with stateless applications. Michigan) in 2002 for use in product life cycle management, it was recently popularized for IoT by Gartner in a 2017 report.

Processing 40

Processing IoT Programming Software Engineering 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

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.

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.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

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. Amazon Redshift) and Elasticsearch machines.

Database 167

Database Lambda AWS IoT 167

Abhishek Tiwari

NOVEMBER 3, 2018

Recently I was asked about content management systems (CMS) of the future - more specifically how they are evolving in the era of microservices, APIs, and serverless computing. Unfortunately, other than cost advantage Wordpress and Drupal have similar deficiencies i.e. legacy monolith architecture.

Systems 63

Systems Cache Website Network 63