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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. 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.

Big Data 321
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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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Kubernetes in the wild report 2023

Dynatrace

The strongest Kubernetes growth areas are security, databases, and CI/CD technologies. 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). Java, Go, and Node.js

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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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Even more amazing papers at VLDB 2019 (that I didn’t have space to cover yet)

The Morning Paper

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. We hear a lot from Google and Microsoft about their cloud platforms, but not quite so much from the other key industry players. What’s their secret??? Yes please!

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

Abhishek Tiwari

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.