Benchmarking Cache Code Storage 
Scalegrid
MARCH 28, 2024
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.
Scalegrid
JANUARY 25, 2024
Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. <code> 127.0.0.1:6379> <code> 127.0.0.1:6379>
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HammerDB
APRIL 19, 2023
As database performance is heavily influenced by the performance of storage, network, memory, and processors, we must understand the upper limit of these key components. For storage, FIO is generally used. Benchmarking the target Two of the more popular database benchmarks for MySQL are HammerDB and sysbench. 0.42 %sys 9.52
Percona
DECEMBER 23, 2022
I wrote this post on MyRocks because I believe it is the most interesting new MySQL storage engine to have appeared over the last few years. The use case is the TPC-C benchmark but executed not on a high-end server but on a lower-spec virtual machine that is I/O limited like for example, with AWS EBS volumes.
Smashing Magazine
SEPTEMBER 28, 2022
Every unnecessary bit of JavaScript code you bundle and serve will be more code the client has to load and process. On your first try, you can use it as a benchmark for optimizations later. How will you serve blazingly fast code, then? Active Memory Caching. Using the cache as permanent storage is an anti-pattern.
HammerDB
JUNE 27, 2022
HammerDB is a software application for database benchmarking. Databases are highly sophisticated software, and to design and run a fair benchmark workload is a complex undertaking. The Transaction Processing Performance Council (TPC) was founded to bring standards to database benchmarking, and the history of the TPC can be found here.
ScaleOut Software
MAY 15, 2014
We have spent a great deal of time at ScaleOut Software re-architecting our in-memory data grid (IMDG)’s code base to make best use of many cores and large memory. For example, the IMDG must be able to efficiently create millions of objects in each server to make use of its huge storage capacity. Testing Scale-Up Performance.
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