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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. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
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MySQL Data Caching Efficiency

Percona

A shared characteristic in most (if not all) databases, be them traditional relational databases like Oracle, MySQL, and PostgreSQL or some kind of NoSQL-style database like MongoDB, is the use of a caching mechanism to keep (a copy of) part of the data in memory. How do you know if your MySQL database caching is operating efficiently?

Cache 90
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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. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 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. Unlike data warehouses, however, data is not transformed before landing in storage.

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Redis® Monitoring Strategies for 2024

Scalegrid

To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold. This ensures each Redis® instance optimally uses the in-memory data store and aligns with the operating system’s efficiency.

Strategy 130
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Elasticsearch Indexing Strategy in Asset Management Platform (AMP)

The Netflix TechBlog

are stored in secure storage layers. Amsterdam is built on top of three storage layers. And finally, we have an Apache Iceberg layer which stores assets in a denormalized fashion to help answer heavy queries for analytics use cases. It is also responsible for asset discovery, validation, sharing, and for triggering workflows.

Strategy 258
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Procella: unifying serving and analytical data at YouTube

The Morning Paper

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., When each of those use cases is powered by a dedicated back-end, investments in better performance, improved scalability and efficiency etc. Cache all the things. Cache all the things. VLDB’19. are divided. Making Procella fast.