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MySQL on Azure Performance Benchmark – ScaleGrid vs. Azure Database

Scalegrid

MySQL Azure Performance Benchmark. In this benchmark report, we compare MySQL hosting on Azure at ScaleGrid vs. Azure Database for MySQL across these three workload scenarios: Read-Intensive Workload: 80% reads and 20% writes. Benchmark configurations. Just getting started? MySQL Read-Intensive Performance.

Azure 299
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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

An application example is a session store recording recent actions. Application example: photo tagging; add a tag is an update, but most operations are to read tags. Application example: user profile cache, where profiles are constructed elsewhere (e.g., Application example: user status updates; people want to read the latest.

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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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Industry page speed benchmarks (March 2022)

Speed Curve

Page Speed Benchmarks is an interactive dashboard that lets you explore and compare web performance data for leading websites across several industries – from retail to media – over the past year. For example: LA Times home page had a Start Render time of 2.5 You can see examples of this above. Testing details.

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HammerDB v4.7 New Features Pt 2: Example CLI Scripts

HammerDB

Docker build, example CLI scripts were added to build and run the TPROC-C workload in the Tcl language. This post will give an overview of the example CLI scripts that you can run directly or use as a template to write your own. Linux example For a first example we will look at the TPROC-C workload in Tcl running on MariaDB on Linux.

C++ 83
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Benchmarking spreadsheet systems

The Morning Paper

Benchmarking spreadsheet systems Rahman et al., Increasingly we’re dealing with larger and larger datasets — for example, data imported via csv files — and spreadsheets are creaking. construct a set of benchmarks to try and understand what might be going on under the covers in Microsoft Excel, Google Sheets, and LibreOffice Calc.

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Implementing service-level objectives to improve software quality

Dynatrace

Instead, they can ensure that services comport with the pre-established benchmarks. Using data from Dynatrace and its SLO wizard , teams can easily benchmark meaningful, user-based reliability measurements and establish error budgets to implement SLOs that meet business objectives and drive greater DevOps automation. Saturation.

Software 272