One of our customers sometimes observed lots of simple insertions taking far longer than expected to complete. Usually these insertions completed in milliseconds, but the insertions sometimes were taking hundreds of seconds. These stalls indicated the existence of a serialization bug in the Fractal Tree index software, so the hunt was on. We found […]Read more
Recently, we’ve seen a few people ask us about building TokuMX from scratch. While it’s best if you just use the binaries you can get from us (they have all the right optimizations, we’ve tested them, and we can interpret coredumps they generate), we recognize there are other reasons you might need to do […]Read more
On Wednesday night, the Boston MongoDB User group was kind enough to have me speak about TokuMX Internals. I spoke about Fractal Tree® indexes and the technical reasons behind the benefits they provide to MongoDB applications. Although the talk mostly references TokuMX and MongoDB, all the theory applies to TokuDB and MySQL as well.
My slides […]
Before creating a unique index in TokuMX or TokuDB, ask yourself, “does my application really depend on the database enforcing uniqueness of this key?” If the answer is ANYTHING other than yes, do not declare the index to be unique. Why? Because unique indexes may kill your write performance. In this post, I’ll explain […]Read more
In my last post, I showed what a Fractal Tree® index is at a high level. Once again, the Fractal Tree index is the data structure inside TokuMX and TokuDB, our MongoDB and MySQL products. One of its strengths is the ability to get high levels of compression on the stored data. In this […]Read more
Tokutek is known for its full-featured fast-indexing technology. MongoDB is known for its great document-based data model and ease of use. TokuMX, version 1.0, combines the best of both worlds.
So what, exactly, is TokuMX? The simplest (but incomplete) answer is that TokuMX is MongoDB with all its storage code replaced by Tokutek’s Fractal Tree […]Read more
Over several blog posts, Tim has presented performance results on large data sets of TokuMX, our MongoDB product with fractal tree indexes integrated, side by side with MongoDB. Results look good. We’ve shown improved throughput numbers on a sysbench benchmark, faster load times, and high compression.
So what is TokuMX, and how does it achieve […]
Two months ago I posted a performance comparison running Sysbench on MongoDB versus MongoDB with Fractal Tree Indexes v0.0.2. The benchmark showed a 133% improvement in throughput. Nice, but our engineering team had an effort on our road-map for lock refinement that we believed would really boost our performance, which is now […]Read more
With this version, the source code is now freely available under the GPL License v2. For more details, see our blog here. Open source pioneer Mozilla has been using TokuDB to manage its MySQL-driven Datazilla Data cluster, an open-source system for managing and visualizing performance data.
Date: May 2nd
Time: 2 PM EST / […]
Since we had the pleasure to announce that TokuDB is open source on Monday, it’s been a thrilling ride. With several members of the team out west all week, back on the east coast we’ve been seeing quite a lot of questions, suggestions, and exciting results.
Here are some of the highlights of our first […]Read more