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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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An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems

The Morning Paper

An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems Gan et al., A typical architecture diagram for one of these services looks like this: Suitably armed with a set of benchmark microservices applications, the investigation can begin! Hardware implications.

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How to maximize CPU performance for PostgreSQL 12.0 benchmarks on Linux

HammerDB

HammerDB doesn’t publish competitive database benchmarks, instead we always encourage people to be better informed by running their own. So over at Phoronix some database benchmarks were published showing PostgreSQL 12 Performance With AMD EPYC 7742 vs. Intel Xeon Platinum 8280 Benchmarks . 3823 2694 -- 0 4 4 2864 74.83

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The top 5 reasons to run your own database benchmarks

HammerDB

Some opinions claim that “Benchmarks are meaningless”, “benchmarks are irrelevant” or “benchmarks are nothing like your real applications” However for others “Benchmarks matter,” as they “account for the processing architecture and speed, memory, storage subsystems and the database engine.”

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The Return of the Frame Pointers

Brendan Gregg

To explain this example in more detail: The profiler periodically interrupts software execution, and for those disconnected stacks it happens to be the execution of the kernel software ("vfs*", "ext*", etc.). These partial stacks get grouped together on the left. Click here for a longer explanation. You usually get an extra junk frame.

Java 145
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

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. It depends upon your application workload and its business logic.

Metrics 130
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Why Browsers Get Built

Alex Russell

Examples include Internet Explorer 3-6 as well as Safari on Mac OS X and the first iPhone. Examples include IE 7+ and Safari from 2010-onward. Historical examples have included UC Browser, and more recently, the current crop of "secure enterprise browsers" (Chromium + keyloggers). a failure to "work upstream").