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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. With these goals in mind, two in-memory data stores, Redis and Memcached, have emerged as the top contenders.

Cache 130
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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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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

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. These distributed storage services also play a pivotal role in big data and analytics operations.

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

Dynatrace

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? Data warehouses.

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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., We’re not told how Seer figures out that a major architectural change has happened. An equally large fraction are due to compute contention, followed by network, cache, memory, and disk contention.

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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

When undertaking system migrations, one of the main challenges is establishing confidence and seamlessly transitioning the traffic to the upgraded architecture without adversely impacting the customer experience. It helps expose memory leaks, deadlocks, caching issues, and other system issues.

Traffic 339