Remove 2017 Remove Availability Remove Hardware Remove Tuning
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PostgreSQL vs. Oracle: Difference in Costs, Ease of Use & Functionality

Scalegrid

Compare PostgreSQL vs. Oracle functionality across available tools, capabilities and services. Compare ease of use across compatibility, extensions, tuning, operating systems, languages and support providers. Not available. Not available. Not available. Compare Functionality. Compare Ease of Use. Total Cost. $0.

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Why Waits Alone Are Not Enough

SQL Performance

Tom Davidson, Opening Microsoft's Performance-Tuning Toolbox SQL Server Pro Magazine, December 2003. Waits and Queues has been used as a SQL Server performance tuning methodology since Tom Davidson published the above article as well as the well-known SQL Server 2005 Waits and Queues whitepaper in 2006. Query Store 2017 to the Rescue.

Tuning 115
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Solaris to Linux Migration 2017

Brendan Gregg

What follows are topics that may be of interest to anyone looking to migrate their systems and skillset: scan these to find topics that interest you. ## ZFS ZFS is available for Linux via the [zfsonlinux] and [OpenZFS] projects, and more recently was included in Canonical's Ubuntu Linux distribution: Ubuntu Xenial 16.04 LTS (April 2016).

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The Speed of Time

Brendan Gregg

As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. Checking those available: $ cat /sys/devices/system/clocksource/clocksource0/available_clocksource. Theory (A) is most likely based on the frame widths in the flame graph. But I'm not completely sure.

Speed 126
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Finding Distinct Values Quickly

SQL Performance

Back in 2014, I wrote an article called Performance Tuning the Whole Query Plan. It has 32GB RAM, with 24GB available to the SQL Server 2019 instance. The parallel column store aggregate push down result of 57 million rows processed in 7ms (using 40ms of CPU) is remarkable, especially considering the hardware. Final Thoughts.

Servers 86
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The Ultimate Guide to MySQL Partitions

Percona

This blog was originally published in July 2017 and was updated in August 2023. This means that multiple partitions can be processed simultaneously, making better use of available hardware resources and further enhancing query performance. This helps identify potential issues and fine-tune the partitioning strategy.

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Using Parallel Query with Amazon Aurora for MySQL

Percona

On multi-core machines – which is the majority of the hardware nowadays – and in the cloud, we have multiple cores available for use. Here is a summary of the queries: Simple queries: select count(*) from ontime where flightdate > '2017-01-01'. With faster disks (i.e. AWS Aurora (based on MySQL 5.6)

Cache 46