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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

High performance, query optimization, open source and polymorphic data storage are the major Greenplum advantages. When handling large amounts of complex data, or big data, chances are that your main machine might start getting crushed by all of the data it has to process in order to produce your analytics results.

Big Data 321
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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. The pipelines can be stateful and the engine’s middleware should provide a persistent storage to enable state checkpointing. Interoperability with Hadoop. Pipelining.

Big Data 154
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Optimizing data warehouse storage

The Netflix TechBlog

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 208
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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
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What is cloud monitoring? How to improve your full-stack visibility

Dynatrace

As cloud and big data complexity scales beyond the ability of traditional monitoring tools to handle, next-generation cloud monitoring and observability are becoming necessities for IT teams. With agent monitoring, third-party software collects data and reports from the component that’s attached to the agent.

Cloud 295
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Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes. The number and variety of applications, network devices, serverless functions, and ephemeral containers grows continuously. Teams have introduced workarounds to reduce storage costs.

Analytics 264
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What is container orchestration?

Dynatrace

But managing the deployment, modification, networking, and scaling of multiple containers can quickly outstrip the capabilities of development and operations teams. This orchestration includes provisioning, scheduling, networking, ensuring availability, and monitoring container lifecycles. How does container orchestration work?