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 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Designed to help scalable applications deliver high performance, it stores live, fast-changing data in memory (DRAM) for fast updates and retrieval. It also transparently makes use of the IMDG’s scalable computing resources to accelerate the analysis.

Analytics 52

Analytics Airlines Cache Scalability 52

Scalegrid

JANUARY 12, 2024

Strategic allocation of these resources plays a crucial role in achieving scalability, cost savings, improved performance, and staying ahead of advancements in the field. This also aids scalability down the line. This includes zero-day vulnerabilities and software weaknesses that are not yet known and can be exploited without warning.

Cloud 130

Cloud Virtualization Storage Efficiency 130

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Designed to help scalable applications deliver high performance, it stores live, fast-changing data in memory (DRAM) for fast updates and retrieval. It also transparently makes use of the IMDG’s scalable computing resources to accelerate the analysis.

Analytics 52

Analytics Airlines Cache Scalability 52

Scalegrid

DECEMBER 6, 2023

ScaleGrid’s comprehensive solutions provide automated efficiency and cost reduction while offering tailored features such as predictive analytics for businesses of all sizes. Traditional self-managed ones give organizations full control over their database infrastructure, such as picking the software and scaling it up.

Database 130

Database Cloud Hardware Storage 130

Dynatrace

NOVEMBER 10, 2022

To take full advantage of the scalability, flexibility, and resilience of cloud platforms, organizations need to build or rearchitect applications around a cloud-native architecture. To better understand cloud-native architecture, it helps to look at each component individually: Software containers. Service mesh.

Cloud 162

Cloud Architecture Serverless Infrastructure 162

ScaleOut Software

JANUARY 31, 2020

Real-time digital twins offer a compelling new software model for tracking and analyzing telemetry from large numbers of data sources. These query results are then forwarded to a data lake for offline analytics using tools such as Spark and for data visualization.

Analytics 59

Analytics Social Media Ecommerce Serverless 59

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

JANUARY 31, 2020

Real-time digital twins offer a compelling new software model for tracking and analyzing telemetry from large numbers of data sources. These query results are then forwarded to a data lake for offline analytics using tools such as Spark and for data visualization.

Analytics 52

Analytics Social Media Serverless Cloud 52

ScaleOut Software

AUGUST 5, 2020

And how are they different from streaming pipelines like Azure Stream Analytics and Apache Flink/Beam? What Problems Does Streaming Analytics Solve? To understand why we need real-time digital twins for streaming analytics, we first need to look at what problems are tackled by popular streaming platforms.

Analytics 69

Analytics Azure Processing Speed 69

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

HammerDB

FEBRUARY 25, 2021

However, it is crucial that the benchmarking application does not have inherent bottlenecks that artificially limits the scalability of the database. This is why the choice of programming language is so important from the outset. Basic Benchmarking Concepts. To benchmark a database we introduce the concept of a Virtual User.

Programming 67

Programming Benchmarking Virtualization C++ 67

ScaleOut Software

JANUARY 28, 2021

Agile In-Memory Software Can Track the Dynamic Rollout of Vaccine Distribution and Delivery to Quickly Spot Problems. Given the unique and highly dynamic nature of this challenge, we need software solutions that are agile enough to adapt to evolving needs and scalable enough to quickly handle a daunting amount of fast-changing data.

Logistics 84

Logistics Airlines Analytics Ecommerce 84

Dynatrace

OCTOBER 17, 2023

Grail is designed for scalability, with no technical prerequisites or additional hosting and storage costs as ingestion rates increase. This phase covers bringing your data into Dynatrace software as a service (SaaS) via whichever ingestion channel or method. Ingest and process. Transparency.

Retail 242

Retail Storage Best Practices Architecture 242

Percona

MARCH 30, 2023

In fact, the opposite is true, thanks to an active and vibrant global community of developers who work continuously to improve open source software. For example, an analytics application would work best with unstructured image files stored in a non-relational graph database.

Open Source 73

Open Source Database Storage Scalability 73

HammerDB

JUNE 27, 2022

HammerDB is a software application for database benchmarking. It enables the user to measure database performance and make comparative judgements about database hardware and software. Databases are highly sophisticated software, and to design and run a fair benchmark workload is a complex undertaking. The HammerDB name.

Benchmarking 62

Benchmarking Open Source C++ Cache 62

ScaleOut Software

JUNE 22, 2020

In general terms, in-memory computing refers to the related concepts of (a) storing fast-changing data in primary memory instead of in secondary storage and (b) employing scalable computing techniques to distribute a workload across a cluster of servers.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ScaleOut Software

JUNE 22, 2020

In general terms, in-memory computing refers to the related concepts of (a) storing fast-changing data in primary memory instead of in secondary storage and (b) employing scalable computing techniques to distribute a workload across a cluster of servers.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

Dynatrace

NOVEMBER 3, 2021

Monitoring , by textbook definition, is the process of collecting, analyzing, and using information to track a program’s progress toward reaching its objectives and to guide management decisions. DevOps practitioners struggle to maintain highly available and scalable applications. Monitoring focuses on watching specific metrics.

Monitoring 226

Monitoring Metrics DevOps Scalability 226

Tasktop

OCTOBER 20, 2020

federal government, IT and program leaders must find a better way to manage their software delivery organizations to improve decision-making where it matters. From AI to the cloud, to predictive analytics and innovative systems, there are few places that software isn’t impacting the government. Think Big, Start Small.

Government 105

Government Programming Metrics Software 105

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

ScaleOut Software

NOVEMBER 24, 2020

Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks. This telematics architecture has evolved to handle ever increasing message rates (often reaching 2K messages per second), make up-to-the-minute information available to dispatchers, and feed offline analytics.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Percona

JUNE 4, 2023

Due to concerns in the open source software community about the future of MySQL after the acquisition, MariaDB was created in 2009 by Michael Widenius (one of the original creators of MySQL), who named the new software after his daughter Maria. Elevate your MariaDB environment with Percona Support for MariaDB. Contact us to learn more!

Open Source 52

Open Source Servers Storage Scalability 52

All Things Distributed

DECEMBER 13, 2016

GoSquared provides various analytics services that web and mobile companies can use to understand their customers' behaviors. At re:Invent 2016 , AWS announced Greengrass (in limited preview), a new service designed to extend the AWS programming model to small, simple, field-based devices. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

ScaleOut Software

MAY 6, 2020

Writing applications for streaming analytics can be complex and time consuming. Existing programming models make it too difficult to perform meaningful analysis in real time. This application cannot be implemented by most streaming analytics platforms. A database service to host state information for each user. Summing Up.

Development 52

Development Analytics Database Programming 52

ScaleOut Software

APRIL 3, 2020

What’s missing is a flexible, fast, and easy-to-use software system that can be quickly adapted to track these assets in real time and provide immediate answers for logistics managers. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

What’s missing is a flexible, fast, and easy-to-use software system that can be quickly adapted to track these assets in real time and provide immediate answers for logistics managers. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

MAY 6, 2020

Writing applications for streaming analytics can be complex and time consuming. Existing programming models make it too difficult to perform meaningful analysis in real time. This application cannot be implemented by most streaming analytics platforms. A database service to host state information for each user. Summing Up.

Development 52

Development Analytics Database Programming 52

The Netflix TechBlog

MAY 21, 2019

There are several problems efficient test scheduling could help us solve: Quickly detect a regression in the integration of the Netflix SDK on a consumer electronic or MVPD (multichannel video programming distributor) device. We wanted the to tool be available as a standalone library as well as scalable API service.

Testing 163

Testing AWS Lambda Network 163

Dotcom-Montior

NOVEMBER 24, 2021

With the rapid advancements in web application technologies, programming languages, cloud computing services, microservices, hybrid environments, etc., This complexity is “hidden” to the end user, like how an API (Application Programming Interface) operates, whether that is an actual user or another computer. Scalability.

Systems 74

Systems Monitoring Hardware Network 74

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

All Things Distributed

SEPTEMBER 6, 2013

Shell leverages AWS for big data analytics to help achieve these goals. Unilever – Unilever R&D program intended to accelerate the company’s scientific progress through improved access to global information. Shell''s scientists, especially the geophysicists and drilling engineers, frequently use cloud computing to run models.

Cloud 129

Cloud Energy AWS Healthcare 129

Testsigma

JULY 13, 2021

A few years back, “ codeless testing ” was interchangeably used with the “ record-and-replay ” functionality of the automation software. Codeless testing is a type of software testing that requires no code writings from the testers. With methods allowing faster software development, testing might get a bit unsynchronised with it.

Testing 52

Testing Artificial Intelligence Programming Code 52

ScaleOut Software

DECEMBER 10, 2019

In its usage in streaming analytics, a real-time digital twin hosts an application-defined method for analyzing event messages from a single data source combined with an associated data object: The data object holds dynamic, contextual information about a single data source and the evolving results derived from analyzing incoming telemetry.

Code 52

Code Analytics Healthcare IoT 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

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., Also, you can choose to program post-commit actions, such as running aggregate analytical functions or updating other dependent tables.

Database 167

Database Lambda AWS IoT 167