There is obviously much being written these days about Big Data. While the term has many different meanings to many different folks, our MySQL and MariaDB customers tend to find their data to be uncomfortably big when the tables become too large for memory. In this case, more storage has to be acquired, performance starts to lag, and making changes to the schema becomes a challenge.

TokuDB addresses these issues for big MySQL instances by delivering high compression rates, faster insertion and query performance, and agile …

It certainly has been a tough week on the East Coast. In the Boston area, where I am located, we got grazed by Sandy – power outages, trees down, schools closed, and Halloween delayed. This though, pales in comparison to what our NY office had to endure. One of our co-founders for example is one of the first few to get his power back at his home on Long Island just yesterday. He considers himself lucky – one of the several pine trees that came down on his property was just a few degrees off from destroying his house (it ended up taking down the gutter instead). Needless to say, it’s going to be a long recovery for NY and NJ. If you are looking to help, see here.

Of course, NYC is known for its resiliency. The first post-Sandy event at Manhattan’s Javitis Conference Center,  …

This webinar covers the basics of B-trees and Fractal Tree Indexes, the benchmarks we’ve run so far, and the development road map going forward.

Date: November 13th
Time: 2 PM EST / 11 AM PST
REGISTER TODAY

Topics will include:

• What is a Fractal Tree Index?
• How to Fractal Trees compare with B-Trees
• What can a Fractal Tree do for MongoDB performance
• Benchmarks + Gotchas
• What’s next

We look forward to having you join the webinar. We also hope that by sharing these results with the community we will be able to elicit people’s …

At tomorrow’s NoVA MySQL October Meetup, I will give a talk: “Fractal Tree Indexes – Theoretical Overview and Customer Use Cases.” The meetup is 7 pm Tuesday, October 23, 2012, and will be held at AOL Campus HQ in Dulles VA.

Most databases employ B-trees to achieve a good tradeoff between the ability to update data quickly and to search it quickly. It turns out that B-trees are far from the optimum in this tradeoff space. This led to the development at MIT, Rutgers and Stony Brook of Fractal Tree® indexes. Fractal Tree indexes improve MySQL® scalability and query performance by allowing greater insertion rates, supporting rich indexing and offering efficient compression. They can also eliminate operational headaches such as …

Next week I’ll be visiting Moscow to talk at Highload++. The conference will take place during Monday 22nd and Tuesday 23rd at the Radisson hotel. I will be giving my personal version of an indexing talk that my colleagues have given in meetups and conferences in the US.

Highload++ conference is targeted to address the issues of complex high traffic web properties. Most of these sites depend on databases to deliver their content, record the traffic and report the application activities in real time. As I learned early in my career at MySQL, the database schema and in particular the indexing strategy, are critical to achieve the highest possible performance out of the database. I’ll be reviewing the basic strategies to define the right indexes. I will also cover TokuDB’s Fractal Tree® and Cluster …

I’ll be presenting “MongoDB and Fractal Tree Indexes” at MongoDB Boston 2012 on October 24th.  My presentation covers the basics of B-trees and Fractal Tree Indexes, the benchmarks we’ve run so far, and the development road map going forward.

I’ve been to this one day conference twice now and both times came away with a better understanding of MongoDB’s capabilities, use-cases, and many questions answered via their deep technical dives.  I highly recommend current MongoDB users and anyone considering a MongoDB project attend – it appears that seats are still available.

Bradley and I (Michael) gave the tutorial on Data Structures and Algorithms for Big Databases at the 6th XLDB Conference last month.

The tutorial was organized as follows:

• Module 0: Tutorial overview and introductions. We describe an observed (but not necessary) tradeoff in ingestion, querying, and freshness in traditional database.
• Module 1: I/O model and cache-oblivious analysis.
• Module 2: Write-optimized data structures. We give the optimal trade-off between inserts and point queries. We show how to build data structures that lie on this tradeoff curve.
• Module 2 continued: Write-optimized …

The core technology behind Tokutek is based on the academic research by our founders: Michael Bender, Bradley Kuszmaul and Martin Farach-Colton.  They are all still in academia, in addition to their work at Tokutek.

Back in March, the White House kicked off a new Initiative for Big Data.  Last week, the National Science Foundation announced the first interagency grants for this.  Eight awards were given, and our own Michael Bender and Martin Farach-Colton, along with Robert Johnson of Stony Brook University, received one of them.

Through their academic work, they hope to extend our …

Recently, our CTO, Martín Farach-Colton had a chance to talk about scaling MySQL and MariaDB with Roberto Zicari of ODBMS.

In the article, Martin states “While I believe that one size fits most, claims that RDBMS can no longer keep up with modern workloads come in from all directions. When people talk about performance of databases on large systems, the root cause of their concerns is often the performance of the underlying B-tree index.” He also notes how “Fractal Tree Indexes put you on a higher-performing tradeoff curve. Query-optimal write-optimized indexing is all about making general-purpose databases faster. For some of our customers’ workloads, it’s as much as two orders of magnitude faster.”

To read the full article, and to …

Recently, our CEO, John Partridge had a chance to talk about novel database technologies for “Big Data” with Peter Cohan of Forbes.

According to the article, “Fractal Tree indexing is helping organizations analyze big data more efficiently due to its ability to improve database efficiency thanks to faster ‘database insertion speed, quicker input/output performance, operational agility, and data compression.’” As a start-up based on “the  first algorithm-based breakthrough in the database world in 40 years,” Toktuetek is following in the footsteps of firms such as Google and RSA, which also relied on novel algortithm advances as core to their technology.

To read the full article, and to see how Tokutek is helping companies tackle big data, see …