Showing entries 1 to 10 of 30
10 Older Entries »
Displaying posts with tag: B-Tree (reset)
Why Percona Acquired Tokutek: by Peter Zaitsev

It is my pleasure to announce that Percona has acquired Tokutek and will take over development and support for TokuDB® and TokuMX™ as well as the revolutionary Fractal Tree® indexing technology that enables those products to deliver improved performance, reliability and compression for modern Big Data applications.

At Percona we have been working with the Tokutek team since 2009, helping to improve performance and scalability. The TokuDB storage engine has been available for Percona Server for about a year, so joining forces is quite a natural step for us.

Fractal Tree indexing technology—developed by years of data science research at MIT, Stony Brook University and Rutgers University—is the new generation data structure which, for many workloads, leapfrogs traditional B-tree technology which was invented in 1972 (over 40 years ago!).  It is also often …

[Read more]
TokuDB Table Optimization Improvements

Section I: Fractal Tree and Optimization Overview
Tokutek’s Fractal Tree® technology provides fast performance by injecting small messages into buffers inside the Fractal Tree index. This allows writes to be batched, thus eliminating I/O that is required in traditional B-tree indexes for every operation. Additional background information on how Fractal Trees operate can be found in Zardosht Kasheff’s blog entitled, TokuMX Fractal Tree Indexes, What Are They? Don’t be thrown off by the title, Fractal Tree Indexes access data in the same way for TokuDB as they do for TokuMX.

For tables whose workload pattern is a high number of sequential deletes, some operational maintenance is required to ensure consistently fast performance.  If this is not done, delete messages and garbage can exist in the Fractal …

[Read more]
Interview with John Partridge, President & CEO of Tokutek, Inc.

“As the database gets used, shards can grow at an uneven rate and one shard might carry a majority of the load. MongoDB corrects this by balancing shards, but because of MongoDB’s lack of concurrency this operation can stall the database unacceptably.”–John Partridge.

I have interviewed John Partridge, President & CEO of Tokutek, Inc.


Q1. Tokutek recently announced to have eliminated performance issues of MongoDB sharding. What was the problem?

John Partridge: The problem occurs after a shard is created. As the database gets used, shards can grow at an uneven rate and one shard might carry a majority of the load. MongoDB corrects this by balancing shards, but because of MongoDB’s lack of concurrency this operation can stall the database unacceptably (see the …

[Read more]
Thoughts on Small Datum – Part 1

A little background…

When I ventured into sales and marketing (I’m an engineer by education) I learned I would often have to interpret and simply summarize the business value that is sometimes hidden in benchmarks. Simply put, the people who approve the purchase of products like TokuDB® and TokuMX™ appreciate the executive summary.

Therefore, I plan to publish a multipart series here on TokuView where I will share my simple summaries and thoughts on business value for the benchmarks Mark Callaghan (@markcallaghan), a former Google and now Facebook database guru, is publishing on his blog, Small Datum.

I’m going to start with his first benchmark post and work my way forward to …

[Read more]
Slides from Boston MongoDB User Group Meetup on 7/31/13

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 are on our technology overview page, along with other great content.

Opportunities to present technical material to an engaged audience asking tough questions is rare, and much appreciated. So thank you to the Boston MongoDB User group for having …

[Read more]
Why Unique Indexes are Bad

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 why.

Unique indexes are a strange beast: they have no impact on standard databases that use B-Trees, such as MongoDB and MySQL, but may be horribly painful for databases that use write optimized data structures, like TokuMX’s Fractal Tree(R) indexes. How? …

[Read more]
Percona Live Slides and Video Available: The Right Read Optimization is Actually Write Optimization

In April, I got to give a talk at Percona Live, about why The Right Read Optimization is Actually Write Optimization. It was my first industry talk, so I was delighted when someone in the audience said “I feel like I just earned a college credit.”

Box offered to host everyone’s slides from the conference here (mine is here). A big thanks from me to Sheeri Cabral, for recording my talk and posting it online!

The focus of the talk …

[Read more]
TokuDB v6.0: Download Available

TokuDB v6.0 is full of great improvements, like getting rid of slave lag, better compression, improved checkpointing, and support for XA.

I’m happy to announce that TokuDB v6.0 is now generally available and can be downloaded here.

Sysbench Performance

I wanted to take this time to talk about one more under-the-hood goody we’ve added to v6.0. In particular, we’ve been working on our locking schemes and have made …

[Read more]
OLTP and OLAP – Have Your Cake and Eat it Too!

Looks like we’ll be having some more fun at the Percona Live MySQL Conference! In addition to our booth and my colleague Tim’s talk, my lightning talk was accepted. The title is “OLTP and OLAP – Have Your Cake and Eat it Too!” The lightning talks, given in a TBD order, will start Wednesday evening (April 11th) at around 6:30 pm.

Below is the abstract I submitted.


OLTP and OLAP – Have Your Cake and Eat it Too!

[Read more]
FictionPress Selects TokuDB for Consistent Performance and Fast Disaster Recovery


Issues addressed:

  • Support complex and efficient indexes at 100+ million rows.
  • Predicable and consistent performance regardless of data size growth.
  • Fast recovery.

Ensuring Predictable Performance at Scale

The Company:  FictionPress operates both and and is home to over 6 million works of fiction, with millions of writers/readers participating from around the world in over 30 languages

The Challenge: FictionPress offers a number of interactive features to its large user base. These …

[Read more]
Showing entries 1 to 10 of 30
10 Older Entries »