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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

This is guest post by Sachin Sinha who is passionate about data, analytics and machine learning at scale. This article is to simply report the YCSB bench test results in detail for five NoSQL databases namely Redis, MongoDB, Couchbase, Yugabyte and BangDB and compare the result side by side. The latency table for test D is as below.

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HammerDB for Managers

HammerDB

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.

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MySQL Key Performance Indicators (KPI) With PMM

Percona

This includes metrics such as query execution time, the number of queries executed per second, and the utilization of query cache and adaptive hash index. query cache: Disable (query_cache_size: 0, query_cache_type:OFF) innodb_adaptive_hash_index: Check adaptive hash index usage to determine its efficiency.

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Percona Monitoring and Management 2 Scaling and Capacity Planning

Percona

We have tested PMM version 2.33.0 Please note that the focus of these tests was around standard metrics gathering and display, we’ll use a future blog post to benchmark some of the more intensive query analytics (QAN) performance numbers. The CPU usage averaged 24% utilization, as you can see in the above picture.

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Google PageSpeed Insights - Scoring 100/100 with WordPress

KeyCDN

Running speed tests with tools like Google PageSpeed Insights , WebPageTest , or KeyCDN’s Website Speed Test are always a good way to help gauge your website’s performance. We decided to experiment with our test site and after some tweaking, we were easily able to achieve a 100/100 score on PageSpeed Insights.

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The Surprising Effectiveness of Non-Overlapping, Sensitivity-Based Performance Models

John McCalpin

To show that I can criticize my own work as well, here I show that sustained memory bandwidth (using an approximation to the STREAM Benchmark ) is also inadequate as a single figure of metric. (It Here I assumed a particular analytical function for the amount of memory traffic as a function of cache size to scale the bandwidth time.

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HCI Performance testing made easy (Part 3)

n0derunner

Creating a HCI benchmark to simulate multi-tennent workloads. A particular problem occurs when a reporting / analytical workload shares storage with a transactional workload. We supply a pre-configured scenario which we call the DB Colocation test. Time based benchmark actions. Distinct per-VM workload patterns.