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Previous 30 Newer Entries Showing entries 31 to 60 of 112 Next 30 Older Entries

Displaying posts with tag: newsql (reset)

Move over Marcia: Top Ten for 2012
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Well, it’s that time of the year again for top ten lists. There have been many versions showing up on the web the last few days, including Time Magazine’s “Top 10 Everything of 2012″ list, with 55 wide ranging lists!

Last year we started using Google Analytics to see what content for blogs was most popular on Tokutek.com and generated a 2011 top ten list, ending up with a few surprises.  This year saw spikes in some interesting areas as well, including flash performance, NASA and Big Data, and MongoDB.

Without further adieu, here is the top ten list for 2012:

10. Announcing TokuDB v6.1

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Packing for the Holidays
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Every time I visit my family for the holidays, as the date approaches, I find myself filled with dread. It’s nothing sinister, my family’s great, and the season is nice. The reason is simple:

I hate packing.

In fact, I hate both kinds of packing: trip packing, and bit packing. Let me tell you a story about bit packing.

Bit packing

If you’ve ever browsed around the available type attributes in GCC, you may have noticed the entry for “packed”. It seems straightforward enough, and if you’re trying to cram a lot of data in a system (like we do), it can be pretty attractive.

There are plenty

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Yule Blog
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Tired of the same old holiday tunes year after year? Join us as we Rock around the Fractal Tree here at Tokutek.

We’ve fiddled with the chorus; won’t you join us?

Rockin’ around the Fractal Tree
(sung to the tune of Rockin’ around the Christmas Tree)

Rockin’ around the Fractal Tree
As the bits begin to hop
Leaves are full on trees that are not B
Our indexes cannot be stopped

Rockin’ around the Fractal Tree
Let the MySQL spirit ring
Time to compress all into an SSD
And watch out for the Merciless Ming

You will get a sensational feeling when you hear voices singing
“No, not a fable; online changes done with alter table!”
Rockin’ around the Fractal Tree










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Fractal Tree Indexing Overview
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We get a lot of questions about how Fractal Tree indexes work. It’s a write-optimized index with fast queries, but which write-optimized indexing structure is it?

In this ~15 minute video (which uses these slides), I give a quick overview of how they work and what they are good for.

Webinar: Best Practices for a Successful TokuDB Evaluation
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In this webinar we will show step by step how to install, configure, and test TokuDB for a typical performance evaluation. We’ll also be flagging potential pitfalls that can ruin the eval results. It will describe the differences between installing from scratch and replacing an existing MySQL / MariaDB installation. It will also review the most common issues that may arise when running TokuDB binaries.

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

Topics will include:

  • Memory allocation
  • Initial data load
  • Indexing, including clustering indexes
  • compression algorithms

We look forward to having you join



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Scalable Databases for Startups
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One of the great things about the MassTLC unConference is the spontaneity of the ideas. In the morning I ran into an old colleague whose startup was looking at switching databases and struggling with the options. Hence, “Scalable Databases for Startups” seemed like a great topic, so I proposed it, and then was off and running full steam after lunch.

The session brought in a wide variety of firms. While there were several vendors there – Basho, Calpont, InterSystems,

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532x Multikey Index Insertion Performance Increase for MongoDB with Fractal Tree Indexes
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In my three previous MongoDB blogs I wrote about our implementation of Fractal Tree(R) indexes on MongoDB, showing a 10x insertion performance increase, a 268x query performance increase, and a comparison of covered indexes and clustered indexes. These benchmarks show the difference that rich and efficient indexing can make to your MongoDB workload.

Given the high performance of Fractal Tree Indexes, we’ve created a new

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Small Data
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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

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Join us at ad:tech this week
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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, 

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Webinar: MongoDB and Fractal Tree Indexes
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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



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My Talk Next Week at HighLoad++
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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

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Presenting “MongoDB and Fractal Tree Indexes” at MongoDB Boston 2012
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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.

Report on XLDB Tutorial on Data Structures and Algorithms
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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
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First of New NSF Big Data Grants Go to Tokutek Founders
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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

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ODBMS Interview: Scaling MySQL and MariaDB to TBs
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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,

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Forbes: “Tokutek Makes Big Data Dance”
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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

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Webinar: Introduction to TokuDB v6.5
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TokuDB® is a proven solution that scales MySQL® and MariaDB® from GBs to TBs with unmatched insert and query speed, compression, replication performance and online schema flexibility. Tokutek’s recently launched TokuDB v6.5 delivers all of these features and more, not just for HDDs, but also for flash memory.

Originally Aired: October 10th
AVAILABLE ON DEMAND

TokuDB v6.5:

  • Stores 10x More Data – TokuDB delivers 10x compression without any performance degradation. Users can therefore take advantage of much greater amounts of available space without paying more for additional storage.
  • Delivers High Insertion Speed – TokuDB

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Three Ways that Fractal Tree Indexes Improve SSD for MySQL
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Since Fractal Tree indexes turn random writes into sequential writes, it’s easy to see why they offer a big advantage for maintaining indexes on rotating disks. It turns out that that Fractal Tree indexing also offers signficant advantages on SSD. Here are three ways that Fractal Trees improve your life if you use SSDs.

Advantage 1: Index maintenence performance.

The results below show the insertion of 1 billion rows into a table while maintaining three multicolumn secondary indexes. At the end of the test, TokuDB’s insertion rate remained at 14,532 inserts/second whereas InnoDB had dropped to 1,607 inserts/second. That’s a difference of over 9x.

Platform: Centos 5.6; 2x Xeon L5520; 72GB RAM; LSI  [Read more...]
Announcing TokuDB v6.5: Optimized for Flash
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We are excited to announce TokuDB® v6.5, the latest version of Tokutek’s flagship storage engine for MySQL and MariaDB.

This version offers optimization for Flash as well as more hot schema change operations for improved agility.

We’ll be posting more details about the new features and performance, so here’s an overview of what’s in store.

Flash TokuDB v6.5 continues the great Toku-tradition of fast insertions. On flash drives, we show an order-of-magnitude (9x) faster insertion rate than InnoDB. TokuDB’s standard compression works just as well on flash and helps you get the most out of your  [Read more...]
Tokutek CEO Named Innovation All Star
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On Friday our CEO John Partridge was named a “Tech Luminary” in the 17th annual Innovation All Stars award, which is given jointly by Mass High Tech (MHT) and the Boston Business Journal (BBJ). As noted in MHT by the editor, Chris McIntosh, the Luminary designations “reflect deep accomplishment in various technology-related industries.”

For more than 20 years, Tokutek CEO John Partridge has worked with startups in both the Boston area and in Silicon Valley. He joined Tokutek from StreamBase Systems which John co-founded with

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Strange Loop Talk on Indexing
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At next week’s Strange Loop conference, I will give a talk on “Understanding Indexing”. The session is 10 am Monday, September 24th, and will be held in the Midland States Room.

Application performance often depends on how fast a query can respond and query performance almost always depends on good indexing. So one of the quickest and least expensive ways to increase application performance is to optimize the indexes. This talk presents three simple and effective rules on how to construct indexes around queries that result in good performance.

This is a general discussion applicable

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Looking for MongoDB users to test Fractal Tree Indexing
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In my three previous blogs I wrote about our implementation of Fractal Tree Indexes on MongoDB, showing a 10x insertion performance increase, a 268x query performance increase, and a comparison of covered indexes and clustered indexes. The benchmarks show the difference that rich and efficient indexing can make to your MongoDB workload.

It’s one thing for us to benchmark MongoDB + TokuDB and another to measure real world performance. If you are looking for a way to improve the performance or

  [Read more...]
XLDB Tutorial on Data Structures and Algorithms
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Next week Michael and I (Bradley) will be travelling to Silicon Valley to present a tutorial on Data Structures and Algorithms for Big Databases at the 6th XLDB Conference.

The tutorial, which is 4 hours on Monday afternoon, aims to cover the following topics (but it’s looking like we’ll have to drop several items for lack of time.)

This tutorial will explore data structures and algorithms for big databases. The topics include:

  • Data structures including B-trees, Log Structured Merge Trees, and Streaming B-trees.
  • Approximate Query Membership data structures including Bloom filters and cascade filters.
  • Algorithms for join including hash joins and
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MongoDB Index Shootout: Covered Indexes vs. Clustered Fractal Tree Indexes
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In my two previous blogs I wrote about our implementation of Fractal Tree Indexes on MongoDB, showing a 10x insertion performance increase and a 268x query performance increase. MongoDB’s covered indexes can provide some performance benefits over a regular MongoDB index, as they reduce the amount of IO required to satisfy certain queries.  In essence, when all of the fields you are requesting are present in the index key, then MongoDB does not have to go back to the main storage heap to

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268x Query Performance Increase for MongoDB with Fractal Tree Indexes, SAY WHAT?
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Last week I wrote about our 10x insertion performance increase with MongoDB. We’ve continued our experimental integration of Fractal Tree® Indexes into MongoDB, adding support for clustered indexes.  A clustered index stores all non-index fields as the “value” portion of the index, as opposed to a standard MongoDB index that stores a pointer to the document data.  The benefit is that indexed lookups can immediately return any requested values instead of needing to do an additional lookup (and potential disk IOs) for the requested fields.

To create a clustered index you just need to add

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10x Insertion Performance Increase for MongoDB with Fractal Tree Indexes
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The challenge of handling massive data processing workloads has spawned many new innovations and techniques in the database world, from indexing innovations like our Fractal Tree® technology to a myriad of “NoSQL” solutions (here is our Chief Scientist’s perspective). Among the most popular and widely adopted NoSQL solutions is MongoDB and we became curious if our Fractal Tree indexing could offer some advantage when combined with it. The answer seems to be a strong “yes”.

Earlier in the summer we kicked off a small side project and here’s what we did: we implemented a “version 2” IndexInterface as a Fractal Tree index and ran some benchmarks. Note that our integration only affects MongoDB’s secondary indexes;

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Webinar: Introduction to TokuDB
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Businesses increasingly operate in a 24×7 environment, where complex analytics must be performed on live, continuously incoming “Big Data.” To address this, TokuDB has developed Fractal Tree®  technology, a revolutionary new indexing capability that enables SQL databases running advanced web applications to grow from gigabytes to terabytes while improving insert speed, query performance, compression, and enabling zero-downtime schema changes.

Date: September 5th
Time: 2 PM EST / 11 AM PST

REGISTER TODAY

TokuDB is used by MySQL and MariaDB customers worldwide to increase their database performance by 20x-80x on Big Data applications that conventional RDBMS’s cannot handle. Instead


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Dagstuhl Seminar on Database Workload Management
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A few weeks ago Bradley Kuszmaul and I attended the Dagstuhl Seminar on Database Workload Management.

The Dagstuhl computer science research center is (remotely) located in the countryside in Saarland, Germany. The actual building is an 18th Century Manor House, first retooled as an old-age home, and then a computer science research center. Workshop participants typically spend the whole week talking and working together.

Dagstuhl Computer Science Center

Shivnath Babu (Duke University), Goetz Graefe (Hewlett Packard),

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Real World Compression
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Benchmarking is a tricky thing, especially when it comes to compression. Some data compresses quite well while other data does not compress at all. Storing jpeg images in a BLOB column produces 0% compression, but storing the string “AAAAAAAAAAAAAAAAAAAA” in a VARCHAR(20) column produces extremely high (and unrealistic) compression numbers.

This week I was assisting a TokuDB customer understand the insertion performance of TokuDB versus InnoDB and MyISAM for their actual data. The table contained a single VARCHAR(50), multiple INTEGER, one SET, one DECIMAL, and a surrogate primary key.  To support a varied query workload they needed 6 indexes.

Here is an obfuscated schema of the table:

col1 varchar(50) NOT NULL,
col2 int(40) NOT NULL DEFAULT '0',
col3 int(10) NOT NULL DEFAULT '0',
col4 int(10) NOT NULL DEFAULT '0',
col5 int(10) NOT NULL DEFAULT '0',
col6
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Thursday’s Emerging Business Technology Meetup in Boston
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I’ll be presenting TokuDB at the Emerging Business Technology Meetup in Boston this Thursday night at 6pm at 290 Congress St (near South Station).  The meeting topic is “NewSQL: SQL Technologies Keeping NoSQL Promises” and also includes presentations from Akiban and VoltDB.  Each of us will be highlighting our technology and use-cases, with a panel discussion and open Q&A to follow.

This is a well attended group with 102 currently registered for the meeting and room for 48 more.  If you

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