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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

RedisĀ® is an in-memory database that provides blazingly fast performance. This makes it a compelling alternative to disk-based databases when performance is a concern. Redis returns a big list of database metrics when you run the info command on the Redis shell. This blog post lists the important database metrics to monitor.

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How to Assess MySQL Performance

HammerDB

Among the different components of modern software solutions, the database is one of the most critical. There are many times we get asked why some cloud instance performed poorly for their database application and almost always turned out to be some configuration error. For storage, FIO is generally used.

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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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What Adrian Did Next?ā€”?Part 2?ā€”?Sun Microsystems

Adrian Cockcroft

The early days at Sun Cambridge were special, I absorbed a lot about networking and the technical side of the role from my fellow systems engineer Martin Baines, and we were driving all over the region in cool company cars (I had a Citroen BX 16V) selling a really hot product.

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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. When available, it can use hardware level performance counters.

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Upcoming of the learned data structures

Abhishek Tiwari

This is a question recently asked and explored by a team of Google researchers led by Jeff Dean with a major focus on database indexes. More importantly, if this works out well, this could lead to a radical improvement in performance by leveraging hardware trends such as GPUs and TPUs. Learned indexes.