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

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

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., Because real-world IoT applications can track thousands of devices or other entities (e.g.,

IoT 45

IoT Ecommerce Analytics Latency 45

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., Because real-world IoT applications can track thousands of devices or other entities (e.g.,

IoT 40

IoT Ecommerce Analytics Latency 40

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

Dynatrace

JUNE 1, 2021

Application performance monitoring (APM) is the practice of tracking key software application performance metrics using monitoring software and telemetry data. Practitioners use APM to ensure system availability, optimize service performance and response times, and improve user experiences. Application performance management.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

Dynatrace

JULY 6, 2020

Effortlessly optimize Azure database performance. Database-service views provide all the metrics you need to set up high-performance database services. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics. Get a comprehensive view of your batch jobs.

Azure 146

Azure Cloud Big Data Virtualization 146

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. To foster research in these categories, we provide an overview of each of these categories to understand the implications on workload analysis and HW/SW architecture research. interactive AR/VR, gaming and critical decision making).

Wireless 54

Wireless IoT Analytics Architecture 54

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

In addition, real-time information on sales and inventory gives managers new tools that help optimize overall performance and maximize profits. In addition, the platform provides fast, in-memory data storage so that the application can easily and quickly record both telemetry and analytics results for each store.

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. In addition, the platform provides fast, in-memory data storage so that the application can easily and quickly record both telemetry and analytics results for each store.

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. 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.

Logistics 52

Logistics Retail Analytics Azure 52

Adrian Cockcroft

FEBRUARY 13, 2023

SUS302 Optimizing architectures for sustainability — Katja Philipp AWS SA and Szymon Kochanski AWS SA. Partner oriented session getting everyone up to speed on what AWS sees as the customer needs, motivations, business outcomes and architectures around sustainability. SUS209 — there was no talk with this code.

AWS 64

AWS Energy Architecture Programming 64

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

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

ScaleOut Software

AUGUST 20, 2020

This blog post explains how a new software construct called a real-time digital twin running in a cloud-hosted service can create a breakthrough for streaming analytics. A real-time digital twin would take the next step by hosting a predictive analytics algorithm that analyzes changes in these properties.

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

AUGUST 20, 2020

This blog post explains how a new software construct called a real-time digital twin running in a cloud-hosted service can create a breakthrough for streaming analytics. A real-time digital twin would take the next step by hosting a predictive analytics algorithm that analyzes changes in these properties.

Cloud 52

Cloud Development 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 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. It has helped assure that these applications deliver predictably fast performance and scale to meet the demands of growing workloads.

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. It has helped assure that these applications deliver predictably fast performance and scale to meet the demands of growing workloads.

Ecommerce 52

Ecommerce Cache Scalability IoT 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

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.

Database 167

Database Lambda AWS IoT 167

Abhishek Tiwari

NOVEMBER 3, 2018

Most of the CMS vendors dodge questions of evolution by talking about incremental innovation primarily focused on customer experience (CX) such as analytics and personalisation. Unfortunately, other than cost advantage Wordpress and Drupal have similar deficiencies i.e. legacy monolith architecture. Decoupled CMS vs. headless CMS.

Systems 63

Systems Cache Website Network 63

All Things Distributed

NOVEMBER 15, 2016

, “How is my marketing campaign performing?”, The reality is that many traditional BI solutions are built on top of legacy desktop and on-premises architectures that are decades old. Collaboration and sharing of live analytics : Users often want to slice and dice their data and share it in various ways.

Analytics 152

Analytics Availability Media Social Media 152