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Kubernetes in the wild report 2023

Dynatrace

Most Kubernetes clusters in the cloud (73%) are built on top of managed distributions from the hyperscalers like AWS Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE). Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch.

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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

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’s high performance eliminates the challenge most RDBMS have scaling to petabtye levels of data, as they are able to scale linearly to efficiently process data.

Big Data 321
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Where programming languages are headed in 2020

O'Reilly

” Willing also offered a shout-out to the CircuitPython and Mu projects, asking, “Who doesn’t love hardware, blinking LEDs, sensors, and using Mu, a user-friendly editor that is fantastic for adults and kids?” ” Java. It’s mostly good news on the Java front. ” What lies ahead?

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What is IT operations analytics? Extract more data insights from more sources

Dynatrace

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 188
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Hybrid cloud infrastructure explained: Weighing the pros, cons, and complexities

Dynatrace

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.

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Structural Evolutions in Data

O'Reilly

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

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5 data integration trends that will define the future of ETL in 2018

Abhishek Tiwari

In 2018, we will see new data integration patterns those rely either on a shared high-performance distributed storage interface ( Alluxio ) or a common data format ( Apache Arrow ) sitting between compute and storage. For instance, Alluxio, originally known as Tachyon, can potentially use Arrow as its in-memory data structure.