TokuDB® v5.2, the latest version of Tokutek’s flagship storage engine for MySQL and MariaDB, is now available.

This version offers performance enhancements over previous releases, especially for multi-client scale up and point queries, and extends the cases where ALTER TABLE is non-blocking, in particular adding Hot Column Rename.

TokuDB v5.2 maintains all our established advantages: fast trickle load, fast bulk load, fast range queries through clustering indexes, hot schema changes, great compression, no fragmentation, and full MySQL compatibility for ease of installation. See our benchmark page for details.

Multi-client workloads

In TokuDB v5.2, we have reworked our locking scheme to better support multi-client workloads, and as always, we have focused on large databases. How did we do? Let’s check out some …

 
Thanks again to Sheeri Cabral  for having me at the Boston MySQL Meetup on Monday for the talk on “Fractal Tree® Indexes – Theoretical Overview and Customer Use Cases.” The crowd was very interactive, and I appreciated that over 50 people signed up for the event and left some very positive comments and reviews.

In addition, the conversation spilled over late into the night as we made our way over to nearby Mead Hall afterwards for a few drinks, some food, and to continue the discussion.

The presentation is …

First of all, I wish you a happy new year.
Many things happened last year, it was really exciting to be involved in the MySQL ecosystem.
I hope this enthusiasm will be increased this year, up to you !

To start the year, I propose the MySQL[plus] Awards 2011
It will only take 5 minutes to fill out these polls.
Answer with your heart first and then with your experience with some of these tools or services.

Polls will be closed January 31, so, vote now !
For “other” answers, please,  let me a comment with details.

Don’t hesitate to submit proposal for tools or services in the comments.
And, please, share these polls !

Note: There is a poll embedded within this post, …

FictionPress

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 FictionPress.com and FanFiction.net 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 …

It’s almost the end of the year – that means holiday cards, shopping, cooking, parties, and the inevitable year-end top lists (including gems like this one).

In the spirit of end of year list making, we fed our 60+ blogs this year through Google Analytics to find out what our own top ten blogs were (outside of product announcements). So if you missed an episode of the View (TokuView that is) we’ve got a Tokutek Top Ten for you (spoiler alert – they are mostly technical):

10. Cage Match: OldSQL, NoSQL and NewSQL – References to mud …

Limelight Networks

Issue addressed: Managing metadata at exabyte scale

Delivering Agile Storage in the Cloud with Billions of Assets

The Company: Founded in 2001, Limelight Networks, Inc (NASDAQ: LLNW) is an Internet platform and services company that integrates the most business-critical parts of the online content value chain. Limelight’s cloud-based services enable customers to profit from the shift of content and advertising to the online world, from the explosive growth of mobile and connected devices, and from the migration of IT applications and services to the cloud. More than 1,800 customers worldwide use Limelight’s massively scalable services to better engage audiences, optimize advertising, manage and monetize …

At next month’s Boston MySQL Meetup, I will give a talk: “Fractal Tree Indexes – Theoretical Overview and Customer Use Cases.” The meetup is 7 pm Monday, January 9th, 2012, and will be held at MIT Building E51 Room 337e (corner of Ames & Amherst St, Cambridge, MA). Thanks to host Sheeri Cabral for the invitation.

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 …

As a storage engine developer, I am excited for MySQL 5.6. Looking at http://dev.mysql.com/tech-resources/articles/whats-new-in-mysql-5.6.html, there has been plenty of work done to improve the performance of reads in MySQL for all storage engines (provided they take advantage of the new APIs).

What would be great to add is API improvements to increase the performance of writes, and more specifically, updates. For many applications that perform updates, such as applications that do click counting or impression counting, there are significant opportunities for improving write performance.

Take the following example of click counting (or impression counting). You have a website and want to save the number of times links on your website have been clicked. Your table may look something like:


create table …

With the release of TokuDB v5.0 last March, we delivered a powerful and agile storage engine that broke through traditional MySQL scalability and performance barriers. As deployments of TokuDB have grown more varied, one request we have repeatedly heard from customers and prospects, especially in areas such as online advertising, social media, and clickstream analysis, is for improved performance for multi-client workloads.

Tokutek is now pleased to announce limited beta availability for TokuDB v5.2. The latest version of our flagship product offers a significant improvement over TokuDB v5.0 in multi-client scaling as well as performance gains in point queries, range queries, and trickle load speed. There are a host of other smaller changes and improvements that are detailed in our release notes (available to beta participants).

TokuDB continues to lead the field by offering:

• 20x to …

At the le MUG some questions raised on TokuDB, i hope this post will answer more in deph details

InnoDB like any other general purpose RDBMS can be really bad for online back-office with big tables, despite following some usual practice and OLTP normalize schema.

• Having indexes in memory
  
• Touching a minimum set of rows for secondary index scan
  
• Scanning some range in primary key order      
  

This happen frequently when

• The working dataset is growing 2 to 100 times the size of the hardware memory
  
• Joining big tables jumping from secondary indexes to clustered table
  
• Increase concurrency on a big tables with range scan starting from a random point in the PRIMARY KEY   
  

It can be …