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Why you should benchmark your database using stored procedures

HammerDB

HammerDB uses stored procedures to achieve maximum throughput when benchmarking your database. HammerDB has always used stored procedures as a design decision because the original benchmark was implemented as close as possible to the example workload in the TPC-C specification that uses stored procedures. performance advantage.

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InnoDB Performance Optimization Basics

Percona

This blog is in reference to our previous ones for ‘Innodb Performance Optimizations Basics’ 2007 and 2013. Although there have been many blogs about adjusting MySQL variables for better performance since then, I think this topic deserves a blog update since the last update was a decade ago, and MySQL 5.7

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How to maximize CPU performance for PostgreSQL 12.0 benchmarks on Linux

HammerDB

HammerDB doesn’t publish competitive database benchmarks, instead we always encourage people to be better informed by running their own. So over at Phoronix some database benchmarks were published showing PostgreSQL 12 Performance With AMD EPYC 7742 vs. Intel Xeon Platinum 8280 Benchmarks . rc3-custom x86_64).

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MySQL Key Performance Indicators (KPI) With PMM

Percona

As a MySQL database administrator, keeping a close eye on the performance of your MySQL server is crucial to ensure optimal database operations. A monitoring tool like Percona Monitoring and Management (PMM) is a popular choice among open source options for effectively monitoring MySQL performance.

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How To Scale a Single-Host PostgreSQL Database With Citus

Percona

PostgreSQL Cluster One coordinator node citus-coord-01 Three worker nodes citus1 citus2 citus3 Hardware AWS Instance Ubuntu Server 20.04, SSD volume type 64-bit (x86) c5.xlarge And now, execute the benchmark: -- execute the following on the coordinator node pgbench -c 20 -j 3 -T 60 -P 3 pgbench The results are not pretty.

Database 107
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How to Assess MySQL Performance

HammerDB

Predicting application performance is a difficult art, but an important one when choosing the target deployment environment. In this blog, we aim to call out some key considerations when trying to assess MySQL performance for your application. We will not concern ourselves with the raw throughput of workload.

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An analysis of performance evolution of Linux’s core operations

The Morning Paper

An analysis of performance evolution of Linux’s core operations Ren et al., For example: “Red Hat and Suse normally required 6-18 months to optimise the performance an an upstream Linux kernel before it can be released as an enterprise distribution”, and. Google’s data center kernel is carefully performance tuned for their workloads.