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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. On MySQL, we saw a 1.5X

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

You will need to know which monitoring metrics for Redis to watch and a tool to monitor these critical server metrics to ensure its health. Connected_slaves provides information about replication status while Used_memory tracks utilized amount of server’s total capacity. You can pick a smart selection of relevant metrics from these.

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Impact of Querying Table Information From information_schema

Percona

On MySQL and Percona Server for MySQL , there is a schema called information_schema (I_S) which provides information about database tables, views, indexes, and more. Disclaimer : This blog post is meant to show a less-known problem but is not meant to be a serious benchmark. Results for Percona Server for MySQL 5.7

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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. However, simply deploying a monitoring tool is not enough; you need to know which Key Performance Indicators (KPIs) to monitor to gain insights into your MySQL server’s health and performance.

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MySQL Performance Tuning 101: Key Tips to Improve MySQL Database Performance

Percona

This results in expedited query execution, reduced resource utilization, and more efficient exploitation of the available hardware resources. Reduced Resource Usage Optimizing resource-intensive queries and configurations can lead to a reduced burden on your server. Indexing is another powerful technique for query optimization.

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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

Key areas include: Configuration parameter tuning : This tuning involves altering variables such as memory allocation, disk I/O settings, and concurrent connections based on specific hardware and requirements. This not only results in cost savings by minimizing hardware requirements but also has the potential to decrease cloud expenses.

Tuning 52
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How to Assess MySQL Performance

HammerDB

GHz 4th Generation Intel Xeon Scalable processors (code-named Sapphire Rapids) Up to 20% higher compute performance than z1d instances Up to 50 Gbps of networking speed Up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (EBS) We can also verify these capabilities by running some simple benchmarks on the different subsystems.