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. Queries in an IMDG can create interesting performance challenges.

Analytics 52

Analytics Airlines Cache Scalability 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

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. Queries in an IMDG can create interesting performance challenges.

Analytics 52

Analytics Airlines Cache Scalability 52

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis and Memcached both provide high performance with sub-millisecond response times. Managed DBaaS solutions like ScaleGrid.io

Cache 130

Cache Storage Scalability Architecture 130

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

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

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. DBaaS provides streamlined management with maintenance-free operations & enhanced security. These advantages come at an expense.

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. These loosely coupled, lightweight services typically perform a single function and can be chained together into an application. Microservices.

Cloud 162

Cloud Architecture Serverless Infrastructure 162

ScaleOut Software

JANUARY 31, 2020

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. However, real-time digital twins easily bring these capabilities within reach.

Analytics 59

Analytics Social Media Ecommerce Serverless 59

HammerDB

FEBRUARY 25, 2021

On high-performance multi-core systems all the supported databases can return performance in the many millions of transactions per minute. However, it is crucial that the benchmarking application does not have inherent bottlenecks that artificially limits the scalability of the database. Basic Benchmarking Concepts.

Programming 67

Programming Benchmarking Virtualization C++ 67

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 31, 2020

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. However, real-time digital twins easily bring these capabilities within reach.

Analytics 52

Analytics Social Media Serverless Cloud 52

Dynatrace

DECEMBER 15, 2022

While engaging the automatic instrumentation of the Dynatrace OneAgent makes log ingestion automatic and scalable , our customers have set up multiple other log ingestion methods. Fluentd is known for its flexibility and is also highly scalable, which makes it a good choice for high-volume environments. Log ingestion strategy no.

Strategy 171

Strategy AWS Open Source Transportation 171

Dynatrace

OCTOBER 17, 2023

Grail is designed for scalability, with no technical prerequisites or additional hosting and storage costs as ingestion rates increase. This compelling success story underscores how the Dynatrace customer-centric pricing approach can drive efficiency, cost savings, and performance improvements for businesses in any sector.

Retail 226

Retail Storage Best Practices Architecture 226

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. Because monitoring tends to focus on key indicators such as utilization rates and throughput, monitoring indicates overall system performance.

Monitoring 209

Monitoring Metrics DevOps Scalability 209

ScaleOut Software

JANUARY 28, 2021

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. Its two core competencies are speed and scalability.

Logistics 84

Logistics Airlines Analytics Ecommerce 84

HammerDB

JUNE 27, 2022

It enables the user to measure database performance and make comparative judgements about database hardware and software. The Transaction Processing Performance Council (TPC) was founded to bring standards to database benchmarking, and the history of the TPC can be found here. What is HammerDB? Why HammerDB was developed.

Benchmarking 62

Benchmarking Open Source C++ Cache 62

Percona

MARCH 30, 2023

Past trepidation — about perceived vulnerabilities and performance issues — has faded as decision makers realize what an “open source database” really is and what it offers. 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

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

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

Percona

JUNE 4, 2023

MariaDB retains compatibility with MySQL, offers support for different programming languages, including Python, PHP, Java, and Perl, and works with all major open source storage engines such as MyRocks, Aria, and InnoDB. In addition, MariaDB provides optimal scalability options, making it ideal for growing workloads. What is MySQL?

Open Source 52

Open Source Servers Storage Scalability 52

Dynatrace

MAY 22, 2019

Beyond just performance and availability statistics, end-user experience and business metrics are also required. User sessions queries is a powerful tool that increases your analytics capabilities exponentially. User session data analytics at scale with Dynatrace. Dynatrace news.

Analytics 103

Analytics Tuning Metrics Programming 103

The Netflix TechBlog

MAY 21, 2019

Netflix engineers run a series of tests and benchmarks to validate the device across multiple dimensions including compatibility of the device with the Netflix SDK, device performance, audio-video playback quality, license handling, encryption and security. which allows fast deployment times and rapid scalability.

Testing 163

Testing AWS Lambda Network 163

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.

Development 52

Development Analytics Database Programming 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.

Development 52

Development Analytics Database Programming 52

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

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

APRIL 3, 2020

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. 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

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. 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 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