DZone

MAY 14, 2020

The performance claims made and the hype surrounding the Graviton2 had us itching to see how our high-performance database would perform. We are, of course, referring to the Amazon EC2 M6g instances powered by AWS Graviton2 processors. The numbers were quite exciting with the AWS Graviton2 living up to the hype, we hope you enjoy!

AWS 130

AWS Benchmarking Database Performance 130

Dynatrace

MAY 1, 2023

Additionally, ITOA gathers and processes information from applications, services, networks, operating systems, and cloud infrastructure hardware logs in real time. Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information.

Analytics 193

Analytics Artificial Intelligence Big Data Open Source 193

All Things Distributed

JULY 13, 2010

Additionally, many high-end HPC applications take advantage of knowing their in-house hardware platforms to achieve major speedup by exploiting the specific processor architecture. Given the specialized nature of these platforms, they require dedicated resources to maintain and operate and put a big burden on the IT organization.

Cloud 119

Cloud AWS Automotive Latency 119

Dynatrace

JUNE 29, 2022

A hybrid cloud, however, combines public infrastructure and services with on-premises resources or a private data center to create a flexible, interconnected IT environment. Hybrid environments provide more options for storing and analyzing ever-growing volumes of big data and for deploying digital services.

Infrastructure 186

Infrastructure Cloud Azure AWS 186

All Things Distributed

OCTOBER 7, 2015

However, the data infrastructure to collect, store and process data is geared toward developers (e.g., 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. Big data challenges.

Cloud 138

Cloud Big Data AWS Analytics 138

Abhishek Tiwari

DECEMBER 27, 2017

ETL refers to extract, transform, load and it is generally used for data warehousing and data integration. ETL is a product of the relational database era and it has not evolved much in last decade. There are several emerging data trends that will define the future of ETL in 2018. Machine learning meets data integration.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

All Things Distributed

APRIL 4, 2017

After finding it cost prohibitive to use colocation centers in local markets where their users are based, iZettle decided to give up hardware. After migrating, database queries that took six seconds now take three seconds in their AWS infrastructure. That’s 100% faster.

AWS 117

AWS Airlines Latency Games 117

The Morning Paper

SEPTEMBER 19, 2019

MongoDB is an important database, and this paper explains the tunable (per-operation) consistency models that MongoDB provides and how they are implemented under the covers. Microsoft have a paper describing their new recovery mechanism in Azure SQL Database , the key feature being that it can recovery in constant time.

Blockchain 46

Blockchain Hardware Google Analytics 46

All Things Distributed

NOVEMBER 15, 2010

This lead to the birth of the Graphics Processing Unit (GPU) which was focused on providing a very fine grained parallel model, with processing organized in multiple stages, where the data would flow through. a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. General Purpose GPU programming.

AWS 136

AWS Latency Programming Architecture 136

All Things Distributed

NOVEMBER 15, 2016

They require companies to provision and maintain complex hardware infrastructure and invest in expensive software licenses, maintenance fees, and support fees that cost upwards of thousands of dollars per user per year. Customers can visualize their data by picking a table and then getting to a visualization in just a few clicks.

Analytics 152

Analytics Availability Media Social Media 152