Santa Clara, California | April 23th – 25th, 2018

Percona Live 2018Percona Live 2018

Santa Clara, California | April 23rd – 25th, 2018

Santa Clara, California | April 23th – 25th, 2018

Percona Live 2018Amazon Aurora MySQL

and RDS MySQL: Lessons Learned

Mariella Di Giacomo

Inspire everyone to use both Amazon RDS MySQL and Aurora MySQL to take

advantage of their numerous capabilitiesClick to at

Goal

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Outline

• Introduction to the main features of Amazon RDS MySQL and Amazon Aurora MySQL

• Introduction of Benchmark

• Brief description of the chosen benchmark suite for the product performance evaluation (using some specific use cases and environments)

• Explanation of the benchmark results through graphs showing the similarities and dissimilarities of the two products (Amazon RDS MySQL and Amazon Aurora MySQL)

• Conclusions

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Amazon RDS MySQL and Aurora MySQL

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Benchmark Definition

What is the definition of benchmark?

• It is a measurement of the quality of products, programs, strategies and theircomparisons

• It is comparing one's business process and the performance metrics to industry best andbest practices

• It implies also some type of comparison or evaluation through comparison

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Benchmark Definition

What is the definition of benchmarking testing?

• In computing, a benchmark is the act of running a computer program, a set of programs,or other operations, in order to assess the relative performance of an object, normally byrunning a number of standard tests and trials against it

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What to Benchmark

The objects benchmarked are:

• Amazon RDS MySQL 5.7.19

• Amazon Aurora MySQL 5.6.10 (November 2017)

• Amazon Aurora MySQL 5.7.12 (Announced on December 11th, 2017 and brieflyexamined)

• Amazon Node Types (t2medium, r4large, r4xlarge, r48xlarge)

• Use the findings to plan the future solutions

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What to Benchmark

The list of features benchmarked includes:

• Fault Tolerance (multiple zones)

• Reliability

• Scalability

• Performance

• Data Integrity

• Ease of use

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What to Benchmark

The list of the benchmarked SQL use cases includes:

• Uncombined Standard Case (Standard Concurrent Read or Write Statements)

• Combined Standard Case (Standard Concurrent Read and Write Statements)

• Uncombined Complex Case (Complex Concurrent Read or Write Statements)

• Combined Complex Case (Complex Concurrent Read and Write Statements)

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Benchmark Environment

The selected environment where the database benchmark suite was executed includes the following characteristics:

• Amazon Cloud

• Amazon Aurora MySQL

• Amazon RDS MySQL

• Isolated network with a network latency almost invisible to the overall communications

• No system load interference on database and client nodes

• Several Types of Amazon Node Instances

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Benchmark Environment

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Benchmark Environment

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Benchmark Parameters

The list of the database benchmark suite main parameters for this evaluation includes:

• Client Concurrency (N Concurrent Remote Clients generating a steady flow eachlaunching N parallel SQL statements repeated 10 times). The included graphs will showonly a client concurrency of 80. Why the number 80? To include in the evaluation alsothe nodes recommended for small production work loads

• Database SQL Statements

• Database InnoDB Engine

• Read and/or Write Statements

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Database Benchmark Tools

The list of the main available database performance benchmark tools includes:

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Benchmark Results

Summary of Median Values for Write Throughput with 80 Remote Concurrent Clients

Uncombined General Combined General

Uncombined Complex Combined Complex

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Benchmark Results

Summary of Median Values for Read Throughput with 80 Remote Concurrent Clients

Uncombined General Combined General

Uncombined Complex Combined Complex

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Benchmark Results

Summary for Write Throughput with 80 Remote Concurrent Clients

Uncombined General

Uncombined Complex

Combined General

Combined Complex

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Benchmark Results

Summary for Read Throughput with 80 Remote Concurrent ClientsUncombined General

Uncombined Complex

Combined General

Combined Complex

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Conclusions

Based on the evaluation, using the described specific use cases, the chosen instances and parameters, it is possible to deduct:

• Amazon Aurora MySQL overall outperforms Amazon RDS MySQL on writes

• Amazon instance type t2medium looks very appropriate for small and medium workloads

• Amazon instance type r48xlarge appears a good choice for the large and very largeenvironments

• Amazon Aurora MySQL Storage volume is striped across hundreds of storage distributednodes over 3 availability zones

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Conclusions

• Both closed-source products Amazon Aurora MySQL and Amazon RDS MySQL basedon the open source MySQL Edition have proven to be success solutions (fault tolerance,reliability, scalability, data integrity and ease to use) for Amazon cloud environments

• Both delivered as a managed service, have automated administration and interventionimplemented also for node crashes or node defects

• Both have low to zero overall database node maintenance

• Use and enjoy Amazon Aurora MySQL and Amazon RDS MySQL!

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References

• https://aws.amazon.com/rds/mysql

• https://aws.amazon.com/rds/mysql/pricing/

• https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_MySQL.html

• https://aws.amazon.com/aurora/

• https://aws.amazon.com/aurora/pricing/

• https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Aurora.html

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