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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

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. Greenplum features a cost-based query optimizer for large-scale, big data workloads. Greenplum Advantages.

Big Data 321
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How Netflix uses eBPF flow logs at scale for network insight

The Netflix TechBlog

By Alok Tiagi , Hariharan Ananthakrishnan , Ivan Porto Carrero and Keerti Lakshminarayan Netflix has developed a network observability sidecar called Flow Exporter that uses eBPF tracepoints to capture TCP flows at near real time. Without having network visibility, it’s difficult to improve our reliability, security and capacity posture.

Network 325
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Hyper Scale VPC Flow Logs enrichment to provide Network Insight

The Netflix TechBlog

Without having network visibility, it’s not possible to improve our reliability, security and capacity posture. Network Availability: The expected continued growth of our ecosystem makes it difficult to understand our network bottlenecks and potential limits we may be reaching. 43416 5001 52.213.180.42

Network 150
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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. In the previous section, we noted that many distributed query processing algorithms resemble message passing networks. It is conceptually similar to the in-stream processing pipelines.

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.

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

Dynatrace

IT operations analytics is the process of unifying, storing, and contextually analyzing operational data to understand the health of applications, infrastructure, and environments and streamline everyday operations. ITOA collects operational data to identify patterns and anomalies for faster incident management and near-real-time insights.

Analytics 193