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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. It’s architecture was specially designed to manage large-scale data warehouses and business intelligence workloads by giving you the ability to spread your data out across a multitude of servers.

Big Data 321
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What Should You Know About Graph Database’s Scalability?

DZone

Having a distributed and scalable graph database system is highly sought after in many enterprise scenarios. Do Not Be Misled Designing and implementing a scalable graph database system has never been a trivial task.

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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. As a result, the input data typically goes from the data source to the in-stream pipeline via a persistent buffer that allows clients to move their reading pointers back and forth.

Big Data 154
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What is a Distributed Storage System

Scalegrid

Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. Variations within these storage systems are called distributed file systems.

Storage 130
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Kubernetes for Big Data Workloads

Abhishek Tiwari

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.

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What is RabbitMQ Used For

Scalegrid

Integrating such a backend service system supported by RabbitMQ into a web application’s architecture can drastically alter its operational dynamics. It enables the smooth processing of various actions like uploading user content, sending notifications, or performing heavy-duty data operations.

IoT 130
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What is IT operations analytics? Extract more data insights from more sources

Dynatrace

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 200