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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

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. It can achieve impressive performance, handling up to 50 million operations per second.

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MySQL Key Performance Indicators (KPI) With PMM

Percona

Indexing efficiency Monitoring indexing efficiency in MySQL involves analyzing query performance, using EXPLAIN statements, utilizing performance monitoring tools, reviewing error logs, performing regular index maintenance, and benchmarking/testing. This KPI is also directly related to Query Performance and helps improve it.

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Performance Testing - Tools, Steps, and Best Practices

KeyCDN

Web performance is a broad subject, and you’ll find no shortage of performance testing tips and tutorials all over the web. Before you begin tuning your website or application, you must first figure out which metrics matter most to your users and establish some achievable benchmarks. What is Performance Testing?

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Why OpenStack is like a Crowdfunded Viking Movie

VoltDB

Hardware Optimizers” want to get the maximum utilization out of hardware. These systems were designed to have a lifetime of half a decade or more, and rapidly changing hardware meant that the initial deployment had to be sized for 5-7 years out. Latency Optimizers” – need support for very large federated deployments.

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HammerDB v4.0 New Features Pt1: TPROC-C & TPROC-H

HammerDB

A full understanding of why this is important requires some knowledge of the evolution of database hardware and software. The HammerDB TPROC-C workload by design intended as CPU and memory intensive workload derived from TPC-C – so that we get to benchmark at maximum CPU performance at a much smaller database footprint.

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

The Morning Paper

Last time around we looked at the DeathStarBench suite of microservices-based benchmark applications and learned that microservices systems can be especially latency sensitive, and that hotspots can propagate through a microservices architecture in interesting ways. on end-to-end latency) and less than 0.15% on throughput.