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How Caches Become Databases – And Why You Don’t Want This

VoltDB

In the world of databases, data management, and data platforms, this entropy usually takes the form of a simple database or data platform that might be ideal for early use cases evolving (or rather, de volving) into an expensive and unmanageable nightmare due to operational strain from use-case gluttony. How hard can it be?

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The Ultimate Guide to Database High Availability

Percona

To make data count and to ensure cloud computing is unabated, companies and organizations must have highly available databases. This guide provides an overview of what high availability means, the components involved, how to measure high availability, and how to achieve it.

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How RevenueCat Manages Caching for Handling over 1.2 Billion Daily API Requests

InfoQ

RevenueCat extensively uses caching to improve the availability and performance of its product API while ensuring consistency. The company shared its techniques to deliver the platform, which can handle over 1.2 billion daily API requests. By Rafal Gancarz

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Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

Central to this infrastructure is our use of multiple online distributed databases such as Apache Cassandra , a NoSQL database known for its high availability and scalability. Over time as new key-value databases were introduced and service owners launched new use cases, we encountered numerous challenges with datastore misuse.

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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.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources. Observing AI models Running AI models at scale can be resource-intensive.

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Is ANALYZE TABLE Safe on a Busy MySQL Database Server?

Percona

version, like this: ANALYZE TABLE removes the table from the table definition cache, which requires a flush lock. This makes the query wait for any long-running queries to finish but also can trigger cascading waiting for other incoming requests. In short, ANALYZE could lead to nasty stalls in busy production environments. x are all safe.

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