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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. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. Fault-tolerance.

Big Data 154
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What is a Distributed Storage System

Scalegrid

Their design emphasizes increasing availability by spreading out files among different nodes or servers — this approach significantly reduces risks associated with losing or corrupting data due to node failure. This process effectively duplicates essential parts of information to safeguard against potential loss.

Storage 130
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

Data warehouses offer a single storage repository for structured data and provide a source of truth for organizations. However, organizations must structure and store data inputs in a specific format to enable extract, transform, and load processes, and efficiently query this data. Massively parallel processing.

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Redis vs Memcached in 2024

Scalegrid

Redis Data Types and Structures The design of Redis’s data structures emphasizes versatility. It is designed to cache plain text values, offering fast read and write access to frequently accessed data. Advanced Redis Features Showdown Big data center concept, cloud database, server power station of the future.

Cache 130
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What is ITOps? Why IT operations is more crucial than ever in a multicloud world

Dynatrace

In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. This transition to public, private, and hybrid cloud is driving organizations to automate and virtualize IT operations to lower costs and optimize cloud processes and systems. So, what is ITOps? Performance. ITOps vs. AIOps.

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Helios: hyperscale indexing for the cloud & edge – part 1

The Morning Paper

Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. What follows is a discussion of where big data systems might be heading, heavily inspired by the remarks in this paper, but with several of my own thoughts mixed in.

Cloud 104
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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. In this way, no human intervention is required in the remediation process. Multi-objective optimizations. user name).

Tuning 210