There are generally three components to any benchmark project:

1. Create the benchmark application
2. Execute it
3. Publish your results

I assume many people think they want to run more benchmarks but give up since step 2 is extremely consuming as you expand the number of different configurations/scenarios.

I'm hoping that this blog post will encourage more people to dive-in and participate, as I'll be sharing the bash script I used to test the various compression options coming in the MongoDB 3.0 storage engines. It enabled me to run a few different tests against 8 different configurations, recording insertion speed and size-on-disk for each one.

If you're into this sort of thing, please read on and provide any feedback or improvements you can think of. …

The next release of MongoDB includes the ability to select a storage engine, the goal being that different storage engines will have different capabilities/advantages, and user's can select the one most beneficial to their particular use-case. Storage engines are cool. MySQL has offered them for quite a while. One very big difference between the MySQL and MongoDB implementations is that in MySQL the user gets to select a particular storage engine for each table, whereas in MongoDB it's a choice made at server startup. You get a single storage engine for everything on the particular mongod instance. I see pros and cons to each decision, but that's a blog for another day.

In MongoDB 3.0 …

Today is my last day at Tokutek. On Monday I'm starting a new opportunity as VP/Technology at CrunchTime!. If you are a web developer, database developer, or quality assurance engineer in the Boston area and looking for a new opportunity please contact me or visit the CrunchTime! career page.

I've really enjoyed my time at VoltDB and Tokutek. Working for Mike Stonebraker (at VoltDB) was on my career "bucket list" and in these past 3.5 years at Tokutek I've experienced the awesomeness of the MySQL ecosystem and the surging NoSQL database …

A few days ago I wrote about MySQL performance implications of InnoDB isolation modes and I touched briefly upon the bizarre performance regression I found with InnoDB handling a large amount of versions for a single row. Today I wanted to look a bit deeper into the problem, which I also filed as a bug.

First I validated in which conditions the problem happens. It seems to happen only in REPEATABLE-READ isolation mode and only in case there is some hot rows which get many row versions during a benchmark run. For example the problem does NOT happen if I run sysbench with “uniform” distribution.

In terms of concurrent selects it also seems to require some very special conditions – you need to have the connection to let some …

Last month I wrote a blog about the closing of MongoDB ticket SERVER-1240, which brings Collection Level Locking (CLL) to the MMAPV1 storage engine in MongoDB 2.8. In MongoDB 2.6 there is a writer lock at the database level, so each database only allows one writer at a time. In concurrent write workloads, this means that all writers essentially form a single line and do their writes one at a time. In MongoDB 2.8 this lock has been moved to the collection level. Better yet is document level locking, but even though this feature was shown at MongoDB World 2014 it's not going to ship. But it did make for one amazing demo by …

"Should vegetarians open steakhouse restaurants?"

Though someone will probably give me several examples of why they should, I'll argue that they absolutely should not. How can someone who doesn't eat steak convince others to eat at their "steak-only" restaurant?

But this is something a "professional technology benchmarker" (PTB) struggles with on a regular basis. Hello, I'm Tim Callaghan, and I'm a PTB.
professional technology benchmarker, or PTB (noun) : One who compares two technologies as part of their job. One of these technologies is usually the product of the PTB's employer, the other is almost always not. In a past experience I was tasked with comparing the performance of a fully in-memory database with Oracle and MySQL on a "TPC-C like" workload. At the time I was an Oracle expert and working for the in-memory database company, but had never started a single MySQL server in my life. At …

I'm starting off 2015 with the following New Year's Resolution, to improve the state of benchmarking. About a month ago I noticed the following tweet:
Hey @tokutek, please look at this: http://stssoft.com/products/stsdb-4-0/benchmark …. Are the benchmarks rigged or correctly done? I'm curious to know! While I've never met Ian Campbell (@iamic) he certainly knew how to call me to action. I immediately checked out the STSsoft website, the benchmark results page, and the benchmark code itself. My first reaction …

While MongoDB 2.8 introduces a formal storage engine API and brings with it the new WiredTiger storage engine, it also adds collection level locking to the existing memory mapped engine (MMAPV1) which will remain the default engine until MongoDB 3.0, so says Eliot.

The MongoDB community has been waiting a long time for collection level locking, the Jira ticket was created on June 15, 2010. When I saw the following Facebook post I got excited to give it a spin, but unfortunately the results were extremely poor using MongoDB …

I just pushed the new Java based iiBench for MySQL (and Percona Server and MariaDB), the code and documentation are available now in the iibench-mysql Github repo. Pull request are welcome!

The history of iiBench goes back to the early days of Tokutek. Since "indexed insertion" is a strength of Fractal Tree indexes, the first iiBench was created by Tokutek in C++ back in 2008. Mark Callaghan rewrote iiBench in Python, adding several features along the way. His version of iiBench is available in …

October 31, 2014 By Severalnines

When running a MariaDB Cluster or Percona XtraDB Cluster, it is common to use a load balancer to distribute client requests across multiple database nodes. Load balancing SQL requests aims to optimize the usage of the database nodes, maximize throughput, minimize response times and avoid overload of the Galera nodes. 

In this blog post, we’ll take a look at four different open source load balancers, and do a quick benchmark to compare performance:

• HAproxy by HAproxy Technologies
• IPVS by Linux Virtual Server Project
• Galera Load Balancer by Codership
• mysqlproxy by Oracle (alpha)

Note that there are other options out there, e.g. MaxScale from the MariaDB team, that we plan to cover in a future post.

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