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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. Greenplum features a cost-based query optimizer for large-scale, big data workloads.

Big Data 321
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Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes. The number and variety of applications, network devices, serverless functions, and ephemeral containers grows continuously. And this expansion shows no sign of slowing down.

Analytics 234
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What is APM?

Dynatrace

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course, end-users that access these applications – including your customers and employees. appeared first on Dynatrace blog. APM can be referred to as: Application performance monitoring.

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What is Application Performance Monitoring?

Dynatrace

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course end-users that access these applications – including your customers and employees. appeared first on Dynatrace blog. APM can also be referred to as: Application performance management.

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Software Testing Trends 2021 – What can we expect?

Testsigma

But in expectation of the big developments in tech trials for 2021, as we had forecast of last year for 2020 , we are looking forward to renewed hope. The growing demand for IoT-testing is the government’s gradual acceptance of smart cities’ concept, which is why businesses are keen to incorporate IoT into their networks.

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Bringing the Magic of Amazon AI and Alexa to Apps on AWS.

All Things Distributed

Last week, I wrote a blog about helping the machine learning scientist community select the right deep learning framework from among many we support on AWS such as MxNet, TensorFlow, Caffe, etc. in ML and neural networks) and access to vast amounts of data. Summing it all up. As we say in Amazon, we are still in Day 1.

AWS 165