[Millions of Queries per Second: PostgreSQL and MySQL’s Peaceful Battle at Today’s Demanding Workloads](https://www.percona.com/blog/2017/01/06/millions-queries-per-second-postgresql-and-mysql-peaceful-battle-at-modern-demanding-workloads/) This blog compares how PostgreSQL and MySQL handle millions of queries per second. Anastasia: Can open source databases cope with millions of queries per second? Many open source advocates would answer “yes.” However, assertions aren’t enough for well-grounded proof. That’s why in this blog post, we share the benchmark testing results from Alexander Korotkov (CEO of Development, Postgres Professional) and Sveta Smirnova (Principal Technical Services Engineer, Percona). The comparative research of PostgreSQL 9.6 and MySQL 5.7 performance will be especially valuable for environments with multiple databases. The idea behind this research is to provide an honest comparison for the two popular RDBMSs. Sveta and Aleksander wanted to test the most recent versions of both MySQL and PostgreSQL with the same tool, under the same challenging workloads and using the same configuration parameters (where possible). However, because both PostgreSQL and MySQL ecosystems evolved independently, with standard testing tools (pgbench and SysBench) used for each database, it wasn’t an easy journey. The task fell to database experts with years of hands-on experience. Sveta has worked as Senior Principal Technical Support Engineer in the Bugs Verification Group of the MySQL Support Group at Oracle for more than eight years, and since 2015 has worked as a Principal Technical Services Engineer at Percona. Alexander Korotkov is a PostgreSQL major contributor, and the developer of a number PostgreSQL features – including the CREATE ACCESS METHOD command, generic WAL interface, lockfree Pin/UnpinBuffer, index-based search for regular expressions and much more. So we have a pretty decent cast for this particular play! Sveta: Dimitri Kravtchuk regularly publishes detailed benchmarks for MySQL, so my main task wasn’t confirming that MySQL can do millions of queries per second. As our graphs will show, we’ve passed that mark already. As a Support Engineer, I often work with customers who have heterogeneous database environments in their shops, and want to know about the impact of migrating jobs from one database to another. So instead, I found the chance to work with the Postgres Professional company and identify both the strong and weak points of the two databases an excellent opportunity. We wanted to test both databases on the same hardware, using the same tools and tests. We expected to test base functionality, and then work on more detailed comparisons. That way we could compare different real-world use case scenarios and popular options. Spoiler: We are far from the final results. This is the start of a blog series. OpenSource Databases on Big Machines, Series 1: “That Was Close…” PostgreSQL Professional together with Freematiq provided two modern, powerful machines for tests. Hardware configuration: Processors: physical = 4, cores = 72, virtual = 144, hyperthreading = yes Memory: 3.0T Disk speed: about 3K IOPS OS: CentOS 7.1.1503 File system: XFS I also used a smaller Percona machine. Hardware configuration: Processors: physical = 2, cores = 12, virtual = 24, hyperthreading = yes Memory: 251.9G Disk speed: about 33K IOPS OS: Ubuntu 14.04.5 LTS File system: EXT4 Note that machines with smaller numbers of CPU cores and faster disks are more common for MySQL installations than machines with larger numbers of cores. The first thing we needed to agree on is which tool to use. A fair comparison only makes sense if the workloads are as close as possible. The standard PostgreSQL tool for performance tests is pgbench, while for MySQL it’s SysBench. SysBench supports multiple database drivers and scriptable tests in the Lua programming language, so we decided to use this tool for both databases. The initial plan was to convert pgbench tests into SysBench Lua syntax, and then run standard tests on both databases. After initial results, we modified our tests to better examine specific MySQL and PostgreSQL features. I converted pgbench tests into SysBench syntax, and put the tests into an open-database-bench GitHub repository. And then we both faced difficulties. As I wrote already, I also ran the tests on a Percona machine. For this converted test, the results were almost identical: #### Percona machine: ``` OLTP test statistics: transactions: 1000000 (28727.81 per sec.) read/write requests: 5000000 (143639.05 per sec.) other operations: 2000000 (57455.62 per sec.) ``` #### Freematiq machine: ``` OLTP test statistics: transactions: 1000000 (29784.74 per sec.) read/write requests: 5000000 (148923.71 per sec.) other operations: 2000000 (59569.49 per sec.) ``` I started investigating. The only place where the Percona machine was better than Freematiq’s was disk speed. So I started running the pgbench read-only test, which was identical to SysBench’s point select test with full dataset in memory. But this time SysBench used 50% of available CPU resources: ``` PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 4585 smirnova 20 0 0,157t 0,041t 9596 S 7226 1,4 12:27.16 mysqld 8745 smirnova 20 0 1266212 629148 1824 S 7126 0,0 9:22.78 sysbench ``` Alexander, in turn, had issues with SysBench, which could not create a high load on PostgreSQL when prepared statements were used: ``` 93087 korotkov 20 0 9289440 3,718g 2964 S 242,6 0,1 0:32.82 sysbench 93161 korotkov 20 0 32,904g 81612 80208 S 4,0 0,0 0:00.47 postgres 93116 korotkov 20 0 32,904g 80828 79424 S 3,6 0,0 0:00.46 postgres 93118 korotkov 20 0 32,904g 80424 79020 S 3,6 0,0 0:00.47 postgres 93121 korotkov 20 0 32,904g 80720 79312 S 3,6 0,0 0:00.47 postgres 93128 korotkov 20 0 32,904g 77936 76536 S 3,6 0,0 0:00.46 postgres 93130 korotkov 20 0 32,904g 81604 80204 S 3,6 0,0 0:00.47 postgres 93146 korotkov 20 0 32,904g 81112 79704 S 3,6 0,0 0:00.46 postgres ``` We contacted SysBench author Alexey Kopytov, and he fixed MySQL issue. The solution is: - Use SysBench with options --percentile=0 --max-requests=0 (reasonable CPU usage) - Use concurrency_kit branch (better concurrency and Lua processing) - Rewrite Lua scripts to support prepared statements (pull request: https://github.com/akopytov/sysbench/pull/94) - Start both SysBench and mysqld with the jemalloc or tmalloc library pre-loaded A fix for PostgreSQL is on the way. For now, Alexander converted a standard SysBench test into pgbench format and we stuck with it. Not much new for MySQL, but at least we had a baseline for comparison. The next difficulty I faced was the default operating system parameters. To make the long story short, I changed them to the recommended ones (described below): ``` vm.swappiness=1 cpupower frequency-set --governor performance kernel.sched_autogroup_enabled=0 kernel.sched_migration_cost_ns= 5000000 vm.dirty_background_bytes=67108864 vm.dirty_bytes=536870912 IO scheduler [deadline] ``` ....tired of copying ### Here are our comparison results. #### Point SELECTs  - pgsql-9.6 is standard PostgreSQL - pgsql-9.6 + pgxact-align is PostgreSQL with this patch (more details can be found in this blog post) - MySQL-5.7 Dimitri is Oracle’s MySQL Server - MySQL-5.7 Sveta is Percona Server 5.7.15 #### OLTP RO  #### OLTP RW  Sync commit in PostgreSQL is a feature, similar to innodb_flush_log_at_trx_commit=1 in InnoDB, and async commit is similar to innodb_flush_log_at_trx_commit=2. You see that the results are very similar: both databases are developing very fast and work with modern hardware well. ##### MySQL results which show 1024 threads for reference.  OLTP RW with innodb_flush_log_at_trx_commit set to 1 and 2  Anastasia: The initial findings of this research were announced at Percona Live Amsterdam 2016. More findings were added to the second version of the same talk given at Moscow HighLoad++ 2016. Hopefully the third iteration of this talk will be available at Percona Live Open Source Database Conference 2017 in Santa Clara. Stay tuned: the Percona Live Committee is working on the program!