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Bloom Filters: Efficient Data Filtering With Practical Applications

DZone

Bloom filters are probabilistic data structures that allow for efficient testing of an element's membership in a set. Bloom, these data structures have found applications in various fields such as databases, caching, networking, and more. Since their invention in 1970 by Burton H.

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Key Advantages of DBMS for Efficient Data Management

Scalegrid

Enhanced data security, better data integrity, and efficient access to information. Despite initial investment costs, DBMS presents long-term savings and improved efficiency through automated processes, efficient query optimizations, and scalability, contributing to enhanced decision-making and end-user productivity.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Effective management of memory stores with policies like LRU/LFU proactive monitoring of the replication process and advanced metrics such as cache hit ratio and persistence indicators are crucial for ensuring data integrity and optimizing Redis’s performance. Cache Hit Ratio The cache hit ratio represents the efficiency of cache usage.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

While off-the-shelf models assist many organizations in initiating their journeys with generative AI (GenAI), scaling AI for enterprise use presents formidable challenges. Model observability provides visibility into resource consumption and operation costs, aiding in optimization and ensuring the most efficient use of available resources.

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Efficient lock-free durable sets

The Morning Paper

Efficient lock-free durable sets Zuriel et al., Memory might be durable, but… …it is expected that caches and registers will remain volatile. State-of-the-art constructions of durable lock-free sets, denoted Log-Free Data Structures, were recently presented by David et al., OOPSLA’19.

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What is a Distributed Storage System

Scalegrid

It utilizes methodologies like DStore, which takes advantage of underused hard drive space by using it for storing vast amounts of collected datasets while enabling efficient recovery processes. These systems enable vast amounts of data to be spread over multiple nodes, allowing for simultaneous access and boosting processing efficiency.

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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.

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