Azure Database Efficiency IoT 
Dynatrace
APRIL 5, 2021
What is Azure Functions? Similar to AWS Lambda , Azure Functions is a serverless compute service by Microsoft that can run code in response to predetermined events or conditions (triggers), such as an order arriving on an IoT system, or a specific queue receiving a new message. The growth of Azure cloud computing.
Dynatrace
JANUARY 26, 2021
VMware commercialized the idea of virtual machines, and cloud providers embraced the same concept with services like Amazon EC2, Google Compute, and Azure virtual machines. REST APIs, authentication, databases, email, and video processing all have a home on serverless platforms. Creating a prototype (for example, on Azure ).
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Scalegrid
MAY 13, 2020
Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. What is an MPP Database?
Dynatrace
JULY 6, 2020
As adoption rates for Microsoft Azure continue to skyrocket, Dynatrace is developing a deeper integration with the platform to provide even more value to organizations that run their businesses on Azure or use it as a part of their multi-cloud strategy. Azure Batch. Azure DB for MariaDB. Azure DB for MySQL.
Adrian Cockcroft
NOVEMBER 26, 2023
Google Cloud and Microsoft Azure released Scope 3 data in 2021. The last number I saw was “over 20GW”, and Amazon has much better global PPA coverage, including India and China, than Google Cloud and Microsoft Azure, who have very few PPAs in Asia. AWS speaker: T.
ScaleOut Software
JANUARY 9, 2020
To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution. It’s not enough just to pick out interesting events from an aggregated data stream and then send them to a database for offline analysis using Spark.
ScaleOut Software
JANUARY 9, 2020
To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution. It’s not enough just to pick out interesting events from an aggregated data stream and then send them to a database for offline analysis using Spark.
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