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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.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

This blog post lists the important database metrics to monitor. 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.

Metrics 130
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How to Assess MySQL Performance

HammerDB

In this blog, we aim to call out some key considerations when trying to assess MySQL performance for your application. Benchmarking the target Two of the more popular database benchmarks for MySQL are HammerDB and sysbench. Benchmarking the target Two of the more popular database benchmarks for MySQL are HammerDB and sysbench.

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Impact of Querying Table Information From information_schema

Percona

Disclaimer : This blog post is meant to show a less-known problem but is not meant to be a serious benchmark. The percentage in degradation will vary depending on many factors {hardware, workload, number of tables, configuration, etc.}. Setup The setup consists of creating 10K tables with sysbench and adding 20 FKs to 20 tables.

Cache 97
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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

This blog was originally published in August 2018 and was updated in May 2023. In this blog post, we will delve into the world of PostgreSQL performance tuning and establish some basic guidelines for setting database parameters to enhance the performance of your PostgreSQL database, based on the workload.

Tuning 52
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MySQL Key Performance Indicators (KPI) With PMM

Percona

In this blog, we will explore various MySQL KPIs that are basic and essential to track using monitoring tools like PMM. Conclusion In this blog, we discussed the basics of MySQL’s key performance indicators (KPIs) using PMM. This KPI is also directly related to Query Performance and helps improve it.

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Why MySQL Could Be Slow With Large Tables

Percona

16 years ago, our founder Peter Zaitsev covered this topic and some of the points described there are still valid, and we will cover more on this blog. In this blog post, we will review key topics to consider for managing large datasets more efficiently in MySQL. 1 mysql mysql 704M Dec 30 02:28 employees.ibd -rw-r --.