Esther Schindler at CIO.com noticed that open-source databases made a poor showing in a recent Evans Data survey. When she asked Evans Data's founder about it, however, he noted that the problem is not in the databases. The problem (with the survey results) is that open-source developers are more critical of their work than, say, Microsoft administrators:

...[W]hen you pay someone else to supply a box of shrink-wrapped software, you're emotionally distant from it. You may rant about its inadequacies, but you're essentially powerless to change them, and you have no expectation that your personal opinion will affect the product's evolution.

...

Matt Asay has the news that IBM has taken the decision to discontinue the development of the solidDB for MySQL database engine following its acquisition of in-memory database specialist Solid Information Technology. The official announcement is here on SourceForge.

As Dhiren Patel, community relations manager writes: “This in-memory technology, and not Solid?s open source offering, was the key driver behind IBM?s acquisition. As a result, I regret to inform you that, effective immediately, we will not be continuing further development on solidDB for MySQL.”

Given the commercial drivers it is not …

I have previously written couple of posts about OSS and China. You can find the posts here and here .

Now, however I have undertaken a challenge to take the understanding of the emerging opportunities for entrepreneurs and investors in the OSS space in China to the next level.

In January Technology Agency of Finland, TEKES and Ministry of Science and Technology from China discussed about undertaking a study tentatively titled Acceleration of Open Source Software Deployment in China, later Linux Foundation also promised its support. Press release of the undertaking can be found from here .

The report will be made freely available both in English and Chinese …

Short and sweet:

CREATE TABLE parts (
   type CHAR(10) NOT NULL,
   id MEDIUMINT NOT NULL AUTO_INCREMENT,
   description CHAR(30) NOT NULL,
   PRIMARY KEY (type, id)
) ENGINE=MyISAM;

INSERT INTO parts (type, description) VALUES
 ('car part', 'brake'),
 ('car part', 'steering wheel'),
 ('furniture', 'table leg'),
 ('printer', 'toner cartridge'),
 ('furniture', 'shelf');

What would be returned by executing:

SELECT DISTINCT id FROM parts;

(more…)

I'm often asked how one can evaluate IO subsystem (Hard drive RAID or SAN) performance for MySQL needs so I've decided to write some simple steps you can take to get a good feeling about it, it is not perfect but usually can tell you quite a lot of what you should expect from the system.

What I usually look for MySQL is performance in random reads and random writes. Sequential reads and writes are rarely the problem for OLTP workloads, so we will not look at them.

I also prefer to look at performance with O_DIRECT flag set to bypass OS cache. This may execute separate code path in kernel and so has a bit different performance pattern compared to buffered IO (even followed by fsync regularly) , but it allows to easily bypass OS cache both for reads and for writes and so does not require creating large working sets for boxes with significant amounts of memory (or reducing amount of usable memory).

The system I'm testing …

[Updated: 2008-03-05 Jeremy writes to tell that I left out the provenscaling.com contact form submission on the 21st and the blank email with a pdf on the 27th]
[Updated: 2008-03-26 Rob Young from MySQL AB sent me an email on the 17th saying, "We are currently working to implement PayPal to cut down on the email interactions we have in place around our manual fulfillment process. Testing is going well and we should have this implemented in the next few weeks."]

Recently Proven Scaling decided to purchase a MySQL Enterprise subscription. We will be evaluating Enterprise to see if it’s knowledge base is valuable to our customers as a supplement to Proven Scaling’s consulting services.

The subscription process seems remarkably manual on MySQL’s part. It involves them sending us five emails (not counting the mysql.com registration), all of which are from different senders. Some are from people others are automated. Here is a …

Implementing MySQL database in 24/7 environments we typically hope for uniform component performance, or at least would like to be able to control it. Typically this is indeed the case, for example CPU will perform with same performance day and night (unless system management software decides to lower CPU frequency due to overheating).

This is also almost the case with Hard Drives - there are possible performance differences based on where data is stored on the disk, amount of remapped sectors etc. There is also database and file system fragmentation however these also tend to accumulate in predictable fashion.

If you have RAID controller this well may not be the case - to protect your data RAID controller may implement bunch of algorithms which can affect performance dramatically.

For example speaking about PERC5 (LSI MegaRaid) - Pretty typical controller from Dell installed on PowerEdge 1950, 2950 etc you should be …

Our two part article on migrating a MySQL database to Oracle features in Database Journal in January and February of this year.  Take a look and please post your comments!

Migrating From MySQL To Oracle - Part I

Migrating From MySQL To Oracle - Part II

SCO files reorg plan with bankruptcy court. Acquia unveils Drupal commercialization plans. Microsoft expands support for web standards. (and more)

The SCO Group Files Formal Reorganization Plan With Bankruptcy Court, The SCO Group (Press Release)

Acquia Unveils Roadmap to Commercially Supported Drupal, Acquia (Press Release)

Microsoft Expands Support for Web Standards, Microsoft (Press Release)

Sun Microsystems Announces New Role Manager Software; Provides Overview of New Governance, Risk and Compliance …

Sorry for the delay, now on to range queries and lenient updates.  Let’s call them queries and updates, for short.  So far, I’ve shown that B-trees (and any of a number of other data structures) are very far from the “tight bound.” I’ll say a bound is a tight if it’s a lower bound and you can come up with data structure that matches it.

So how do we match the bandwidth bound for queries and updates?  I already mentioned in passing how to do this, but let’s look more closely.

Fast Updates

The way to get fast updates is to log them.  You can easily saturate disk bandwidth by writing out the insertion, deletion and update requests with no index. 

A query now will typically start by sorting the data.  Even a point query requires looking at all the data, but a range query requires looking at all the data log times (in order to sort it), or using a large amount of extra …