Remove Big Data Remove Cache Remove Design Remove Latency
article thumbnail

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. Introduction Caching serves a dual purpose in web development – speeding up client requests and reducing server load.

Cache 130
article thumbnail

In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

What is a Distributed Storage System

Scalegrid

Their design emphasizes increasing availability by spreading out files among different nodes or servers — this approach significantly reduces risks associated with losing or corrupting data due to node failure. By implementing data replication strategies, distributed storage systems achieve greater.

Storage 130
article thumbnail

What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

Data lakehouses deliver the query response with minimal latency. While data lakehouses combine the flexibility and cost-efficiency of data lakes with the querying capabilities of data warehouses, it’s important to understand how these storage environments differ. Data warehouses.

article thumbnail

How LinkedIn Serves Over 4.8 Million Member Profiles per Second

InfoQ

LinkedIn introduced Couchbase as a centralized caching tier for scaling member profile reads to handle increasing traffic that has outgrown their existing database cluster. The new solution achieved over 99% hit rate, helped reduce tail latencies by more than 60% and costs by 10% annually. By Rafal Gancarz

Cache 85
article thumbnail

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

The Morning Paper

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., Finally, we show that Seer can identify application level design bugs, and provide insights on how to better architect microservices to achieve predictable performance. ASPLOS’19.

article thumbnail

Helios: hyperscale indexing for the cloud & edge – part 1

The Morning Paper

Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. What follows is a discussion of where big data systems might be heading, heavily inspired by the remarks in this paper, but with several of my own thoughts mixed in.

Cloud 104