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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

This counting service, built on top of the TimeSeries Abstraction, enables distributed counting at scale while maintaining similar low latency performance. After selecting a mode, users can interact with APIs without needing to worry about the underlying storage mechanisms and counting methods.

Latency 251
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Storage handling improvements increase retention of transaction data for Dynatrace Managed

Dynatrace

Using existing storage resources optimally is key to being able to capture the right data over time. This decompression of data is achieved with minimal impact on performance and costs. Increased storage space availability. Storage quotas defined for your Dynatrace Managed deployment and its environments.

Storage 246
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. Greenplum uses an MPP database design that can help you develop a scalable, high performance deployment.

Big Data 321
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The Power of Caching: Boosting API Performance and Scalability

DZone

Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing. Bandwidth optimization: Caching reduces the amount of data transferred over the network, minimizing bandwidth usage and improving efficiency.

Cache 246
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RabbitMQ vs. Kafka: Key Differences

Scalegrid

This article outlines the key differences in architecture, performance, and use cases to help determine the best fit for your workload. Message brokers handle validation, routing, storage, and delivery, ensuring efficient and reliable communication. What is RabbitMQ?

Latency 147
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Optimize your environment: Unveiling Dynatrace Hyper-V extension for enhanced performance and efficient troubleshooting

Dynatrace

Secondly, determining the correct allocation of resources (CPU, memory, storage) to each virtual machine to ensure optimal performance without over-provisioning can be difficult. This presents a challenge for IT operations teams, specifically in identifying and addressing performance issues or planning how to prevent future issues.

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Top PostgreSQL 17 New Features

Scalegrid

PostgreSQL 17 improves performance, backups, JSON handling, and security. Heres what stands out: Key Takeaways Better Performance: Faster write operations and improved vacuum processes help handle high-concurrency workloads more smoothly. Key Benefits: Smaller Storage Footprint: Saves only modified data, cutting down backup size.

Speed 130