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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.

Big Data 154
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Kubernetes in the wild report 2023

Dynatrace

While Kubernetes is still a relatively young technology, a large majority of global enterprises use it to run business-critical applications in production. Findings provide insights into Kubernetes practitioners’ infrastructure preferences and how they use advanced Kubernetes platform technologies. Java, Go, and Node.js

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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. This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology.

Storage 130
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Driving down the cost of Big-Data analytics - All Things Distributed

All Things Distributed

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. Driving Storage Costs Down for AWS Customers. Comments (). Syndication.

Big Data 112
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The Need for Real-Time Device Tracking

ScaleOut Software

Incoming data is saved into data storage (historian database or log store) for query by operational managers who must attempt to find the highest priority issues that require their attention. The technology that can do this is called in-memory computing. The heavy lifting is deferred to the back office.

IoT 78
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Expanding the Cloud ? Managing Cold Storage with Amazon Glacier

All Things Distributed

Managing Cold Storage with Amazon Glacier. With the introduction of Amazon Glacier , IT organizations now have a solution that removes the headaches of digital archiving and provides extremely low cost storage. Data is retrieved by scheduling a job, which typically completes within 3 to 5 hours. All Things Distributed.

Storage 122
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Why MySQL Could Be Slow With Large Tables

Percona

While the technologies have evolved and matured enough, there are still some people thinking that MySQL is only for small projects or that it can’t perform well with large tables. With disks being faster nowadays and CPU and memory resources being cheaper, we could easily say MySQL can handle TBs of data with good performance.