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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 many cases join is performed on a finite time window or other type of buffer e.g. LFU cache that contains most frequent tuples in the stream. Towards Unified Big Data Processing.

Big Data 154
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Redis vs Memcached in 2024

Scalegrid

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Introduction Caching serves a dual purpose in web development – speeding up client requests and reducing server load.

Cache 130
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Comparing Apache Ignite In-Memory Cache Performance With Hazelcast In-Memory Cache and Java Native Hashmap

DZone

This article compares different options for the in-memory maps and their performances in order for an application to move away from traditional RDBMS tables for frequently accessed data.

Cache 147
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Formulating ‘Out of Memory Kill’ Prediction on the Netflix App as a Machine Learning Problem

The Netflix TechBlog

We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform. With large data, comes the opportunity to leverage the data for predictive and classification based analysis.

Big Data 179
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Kubernetes in the wild report 2023

Dynatrace

Of the organizations in the Kubernetes survey, 71% run databases and caches in Kubernetes, representing a +48% year-over-year increase. Together with messaging systems (+36% growth), organizations are increasingly using databases and caches to persist application workload states.

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What is a Distributed Storage System

Scalegrid

Handling a storage system spread across multiple physical servers introduces complexities such as unpredictability in behavior, difficulties with testing procedures, and an overall increase in administrative complexity due to the dispersed nature of data.

Storage 130
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Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

The Morning Paper

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., An equally large fraction are due to compute contention, followed by network, cache, memory, and disk contention. ASPLOS’19. Distributed tracing and instrumentation.