DZone

MARCH 7, 2023

Apache Spark is a powerful open-source distributed computing framework that provides a variety of APIs to support big data processing. In addition, pySpark applications can be tuned to optimize performance and achieve better execution time, scalability, and resource utilization.

Big Data 173

Big Data Code Tuning Open Source 173

Dynatrace

JANUARY 16, 2023

Open-source software drives a vibrant Kubernetes ecosystem. Through effortless provisioning, a larger number of small hosts provide a cost-effective and scalable platform. Open source software drives a vibrant Kubernetes ecosystem. Dynatrace’s investment in open source technologies keeps growing.

Open Source 337

Open Source Java Operating System Programming 337

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges. Performance.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Dynatrace

MARCH 24, 2023

Originally created by Google, Kubernetes was donated to the CNCF as an open source project. Originally developed as a research project at the University of California, Berkeley, in 2009, Mesos launched formally as a mature product in 2016 under the auspices of the Apache Software Foundation, a decentralized open source community.

Infrastructure 179

Infrastructure Open Source Operating System Cloud 179

Scalegrid

MAY 13, 2020

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. Greenplum uses an MPP database design that can help you develop a scalable, high performance deployment. Open Source. What Exactly is Greenplum?

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

MAY 1, 2023

Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information. Here are the six steps of a typical ITOA process : Define the data infrastructure strategy. Identify data use cases and develop a scalable delivery model with documentation.

Analytics 182

Analytics Artificial Intelligence Big Data Open Source 182

All Things Distributed

SEPTEMBER 6, 2013

Shell leverages AWS for big data analytics to help achieve these goals. Due to the exponential growth of the biology and informatics fields, Unilever needs to maintain this new program within a highly-scalable environment that supports parallel computation and heavy data storage demands.

Cloud 129

Cloud Energy AWS Healthcare 129