Dynatrace

DECEMBER 22, 2019

AWS offers a broad set of global, cloud-based services including computing, storage, networking, Internet of Things (IoT), and many others. Amazon Kinesis Data Analytics. Amazon Simple Storage Service (S3). Dynatrace news. Amazon Elasticsearch Service (ES). Amazon Kinesis Data Firehose. Amazon Kinesis Data Streams (KDS).

AWS 138

AWS Metrics IoT Storage 138

Dynatrace

DECEMBER 22, 2019

AWS offers a broad set of global, cloud-based services including computing, storage, networking, Internet of Things (IoT), and many others. Amazon Kinesis Data Analytics. Amazon Simple Storage Service (S3). Dynatrace news. Amazon Elasticsearch Service (ES). Amazon Kinesis Data Firehose. Amazon Kinesis Data Streams (KDS).

AWS 134

AWS Metrics IoT Storage 134

All Things Distributed

DECEMBER 13, 2016

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

AWS 157

AWS Cloud Artificial Intelligence IoT 157

All Things Distributed

JUNE 21, 2018

Use cases such as gaming, ad tech, and IoT lend themselves particularly well to the key-value data model where the access patterns require low-latency Gets/Puts for known key values. This consistent performance is a big part of why the Snapchat Stories feature , which includes Snapchat's largest storage write workload, moved to DynamoDB.

Database 167

Database AWS Games Latency 167

VoltDB

NOVEMBER 20, 2024

The Need for Real-Time Analytics and Automation With increasing complexity in manufacturing operations, real-time decision-making is essential. With predictive analytics at the edge, machines can be monitored continuously for early signs of wear, allowing for timely maintenance without interrupting production.

IoT 52

IoT Energy Latency Automotive 52

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. 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. The list goes on.

IoT 78

IoT Big Data Analytics Architecture 78

All Things Distributed

JUNE 7, 2017

Some applications – medical equipment, industrial machinery, and building automation are just a few – can't rely exclusively on the cloud for control, and require some form of local storage and execution. Local aggregation and filtering of data allows customers to send only high-value data to the cloud for storage and analysis.

AWS 91

AWS IoT Lambda Storage 91

All Things Distributed

OCTOBER 7, 2015

In AWS’ quest to enable the best data storage options for engineers, we have built several innovative database solutions like Amazon RDS, Amazon RDS for Aurora, Amazon DynamoDB, and Amazon Redshift. SPICE enables QuickSight to scale to many terabytes of analytical data and deliver response time for most visualization queries in milliseconds.

Cloud 116

Cloud Big Data AWS Analytics 116

VoltDB

JUNE 26, 2024

Increased efficiency Leveraging advanced technologies like automation, IoT, AI, and edge computing , intelligent manufacturing streamlines production processes and eliminates inefficiencies, leading to a more profitable operation.

IoT 52

IoT Analytics Artificial Intelligence Energy 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

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

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. In a traditional visual analytics pipeline, we compress the data by exploiting the redundancies in time and space. For many IoT applications involving wireless video sensors (e.g. Quality vs Bandwidth.

Wireless 54

Wireless IoT Analytics Architecture 54

VoltDB

SEPTEMBER 10, 2024

Industrial IoT (IIoT) really means making industrial devices work together so they can communicate better for the sake of ultimately improving data analytics, efficiency, and productivity. As you roll out your UNS, it’s critical to implement strong security measures to keep your sensitive data protected in transit and in storage.

IoT 52

IoT Architecture Scalability Analytics 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. For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing.

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. For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing.

Ecommerce 52

Ecommerce Cache Scalability IoT 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

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. Alternatively, you can upload output directory to cloud object/blob storage such as Amazon S3 or Azure Blob Storage and serve your site from there.

Systems 63

Systems Cache Website Network 63

Testsigma

FEBRUARY 12, 2021

IoT Test Automation. The Internet of Things is generally referred to as IoT which encompasses computers, cars, houses or some other technological system related. There is a huge expansion and the need for a good IoT research plan. . In 2019, we had previously projected the demand for IoT research at $781.96billion.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Adrian Cockcroft

NOVEMBER 18, 2024

Hear how AWS infrastructure is efficient for your AI workloads to minimize environmental impact as you innovate with compute, storage, networking, and more. In this session, learn how Tokio Marine Highland uses CARTO’s spatial analytics platform on AWS to manage climate risk and assess impacts of severe weather to its business.

AWS 98

AWS Energy Lambda Government 98