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How to Scale Elasticsearch to Solve Your Scalability Issues

DZone

With the evolution of modern applications serving increasing needs for real-time data processing and retrieval, scalability does, too. This extra network overhead will easily result in increased latency compared to a single-node architecture where data access is straightforward.

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Scalable Annotation Service?—?Marken

The Netflix TechBlog

Scalable Annotation Service — Marken by Varun Sekhri , Meenakshi Jindal Introduction At Netflix, we have hundreds of micro services each with its own data models or entities. The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency.

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Improve Application Latency With Read Replicas Using YugabyteDB [Video]

DZone

Scalability and low latency are crucial for any application that relies on real-time data. In this post, we'll discuss how you can use YugabyteDB and its read replica nodes to improve the read latency for users across the globe. One way to achieve this is by storing data closer to the users.

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Performance and Scalability Analysis of Redis and Memcached

DZone

Speed and scalability are significant issues today, at least in the application landscape. We compare throughput, operations per second, and latency under different loads, namely the P90 and P99 percentiles. We compare throughput, operations per second, and latency under different loads, namely the P90 and P99 percentiles.

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API Design Principles for Optimal Performance and Scalability

DZone

The goal is to help developers, technical managers, and business owners understand the importance of API performance optimization and how they can improve the speed, scalability, and reliability of their APIs. API performance optimization is the process of improving the speed, scalability, and reliability of APIs.

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RabbitMQ vs. Kafka: Key Differences

Scalegrid

This decoupling simplifies system architecture and supports scalability in distributed environments. Kafka stores and distributes data through a partitioned log system, which spans multiple brokers to provide fault tolerance and scalability. Apache Kafka uses a custom TCP/IP protocol for high throughput and low latency.

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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

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