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InnoDB Performance Optimization Basics

Percona

This blog is in reference to our previous ones for ‘Innodb Performance Optimizations Basics’ 2007 and 2013. By caching hot datasets, indexes, and ongoing changes, InnoDB can provide faster response times and utilize disk IO in a much more optimal way. Typically a good value is 70%-80% of available memory.

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

John McCalpin

This data is from the 2007 presentation. It is not surprising that there is a lot of scatter, but the factor of four range in Peak MFLOPS at fixed SPECfp_rate2000/core and the factor of four range in SPECfp_rate2000/core at fixed Peak MFLOPS was higher than I expected… (Also from the 2007 presentation.)

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A Decade of Dynamo: Powering the next wave of high-performance, internet-scale applications

All Things Distributed

We were pushing the limits of what was a leading commercial database at the time and were unable to sustain the availability, scalability and performance needs that our growing Amazon business demanded. Durable and Highly-Available – DynamoDB maintains data durability and 99.99 This was the genesis of the Amazon Dynamo database.

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Egnyte Architecture: Lessons learned in building and scaling a multi petabyte content platform

High Scalability

Egnyte is a secure Content Collaboration and Data Governance platform, founded in 2007 when Google drive wasn't born and AWS S3 was cost-prohibitive. Edge caching. In general, Egnyte connect architecture shards and caches data at different levels based on: Amount of data. Nginx for disk based caching. Hybrid Sync.

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Progress Delayed Is Progress Denied

Alex Russell

This post mines publicly available data on the pace of compatibility fixes and feature additions to assess the claim. The information it captures is, however, available going back somewhat further, providing a fuller picture of the trend lines of engine completeness. Count of APIs available from JavaScript by Web Confluence.

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