Last week Tokutek announced that they’re open-sourcing their TokuDB storage engine for MySQL. If you’re not familiar with TokuDB, it’s an ACID-compliant storage engine with a high-performance index technology known as fractal tree indexing. Fractal trees have a number of nice characteristics, but perhaps the most interesting is that they deliver consistently high performance under varying conditions, such as when data grows much larger than memory or is updated frequently. B-tree indexes tend to get fragmented over time, and exhibit a performance cliff when data doesn’t fit in memory anymore.

The MySQL community is excited about having access to TokuDB’s source code, and rightly so. TokuDB is, broadly speaking, aimed at the same category of use cases as Oracle’s InnoDB, …

Those who are familiar with me know I've a dream.

5 years ago I decided to leave a systems integrator where I was doing great. Why? I wanted to be in a company with the same growth prospects that Oracle had in the 80s. I dreamed to be in the Oracle of 30 years ago and, as time travel wasn't affordable, I decided to join MySQL AB to help expand the business in Europe, the Middle East and Africa.
A few years later my dream came true, but in a slightly different sense. Sun acquired MySQL and was later swallowed by Oracle giving me the opportunity to join the company I wished I could have helped build.

Oracle is an amazing …

Big news at Percona Live MySQL Conference and Expo this week, Tokutek open sourced TokuDB thus making my previous post Where are they now: MySQL Storage Engines out of date in just a few days.

In this case, I really don’t mind. It’s rather exciting that they’ve gone ahead and done this –  and it’s not just a code drop: https://github.com/Tokutek/ft-engine is where things are at, and recent commits were 2hrs and 18hrs ago which means that this is being maintained. This is certainly a good way to grow a developer community.

While being a MySQL engine is really interesting, the MongoDB integration is certainly something to watch – and may be …

Slides from my Percona Live talk evaluating the new spatial features in MySQL 5.6 and MariaDB 5.5 are now online. This is new material I have never presented before. It is based on work I have done in my job at Nokia HERE.com location services. So even if at this conference it draws less attention than my HA talks, it is actually what I'm most proud of to present.

TL;DR summary is that PostgreSQL has lots of features but MySQL has much better ease of use and performance. (I copy paste this standard sentence into any PostgreSQL vs MySQL evaluation I do :-) The MongoDB info is basically outdated, as the new 2.4 release introduces completely new implementation based on GeoJSON, new indexing, neither of which I tested.

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Earlier, I talked about the transactional semantics we are introducing to MongoDB. As I hinted at the end of the post, we are actually doing more. We are introducing multi-statement transactions. That’s right, multiple queries, updates, deletes, and inserts will be able to run inside of a single transaction. We are working on the details of the semantics as we develop our beta, but at a high level, think of it as having the same semantics as TokuDB and InnoDB’s multi-statement transactions in MySQL.

So how will it work? We introduce three new commands:

db.runCommand({"beginTransaction", "isolation": "mvcc"})

This begins a transaction with the isolation level of MVCC, which means queries will use a snapshot of the system. This is essentially the same as “repeatable-read” in MySQL. Isolations of …

People claim that MongoDB is not transactional. It actually is, and that’s a good thing.

In MongoDB 2.2, individual operations are Atomic. By having per database locks control reads and writes to collections, write operations on collections are Consistent and Isolated. With journaling on, operations may be made Durable. Put these properties together, and you have basic ACID properties for transactions.

The shortcoming with MongoDB’s implementation is that these semantics apply to individual write operations, such as an individual insert or individual update. If a MongoDB statement updates 10 rows, and something goes wrong with the fifth row, then the statement will finish execution with four rows updated and six …

We recently resumed our discussion around bringing Fractal Tree indexes to MongoDB.  This effort includes Tokutek’s interview with Jeff Kelly at Strata as well as my two recent tech blogs which describe the compression achieved on a generic MongoDB data set and performance improvements we measured using on our implementation of Sysbench for MongoDB.  I have a full line-up of benchmarks and blogs planned for the next few months, as our project continues.  Many of these will be deeply technical and written by the Tokutek developers.

We have a group …

As we continue to test our Fractal Tree Indexing with MongoDB, I’ve been updating my benchmark infrastructure so I can compare performance, correctness, and resource utilization.  Sysbench has long been a standard for testing MySQL performance, so I created a version that is compatible with MongoDB.  You can grab my current version of Sysbench for MongoDB here.

So what exactly is Sysbench?  According to the Sysbench homepage, “Sysbench is a modular, cross-platform and multi-threaded benchmark tool for evaluating OS [Operating System] parameters that are important for a system running a database under intensive load.”

• Sysbench schema
  • 16 copies of the same collection, named sbtest1 … sbtest16, each with 10 …

During the second half of our CUBE discussion with Wikibon analyst Jeff Kelly at this year’s Strata Conference in Santa Clara, we talked about the tipping point for Big Data. Strata veterans could see at a glance that this year’s conference was markedly different. No longer the exclusive domain of geeks and database administrators, this year’s Strata featured some of the biggest enterprise vendors around. With heavy weight enterprise players Intel and EMC Greenplum announcing their own Hadoop distributions, big data is clearly going mainstream. Now that we know how to capture, store, access and analyze big data, what’s the next step? Listen in to hear my conversation with Jeff Kelly about taking big data down its last mile and finally putting it in the hands of business users.

Source: …

We had the opportunity to do a CUBE interview with Wikibon analyst Jeff Kelly at last week’s Strata Conference in Santa Clara. In the first part of our conversation, we discuss how our success in integrating Tokutek’s Fractal Tree® technology into MySQL has led us to another popular database, MongoDB. We explain the results of our recent benchmarking tests with MongoDB, which indicate that adding indexing can also improve performance for this popular NoSQL database with faster insertion rates, lower query latency and greater …