High Performance MySQL, 3rd Edition has been selling very well. It’s translated into many languages. O’Reilly sends me a hard-copy of the translations, and I have a whole section on my bookshelf dedicated to them. It’s really satisfying to look at it.

Today I’m happy to announce that we’re moving forward with a new batch of translations. Demand has been so strong that we want to make the book accessible to as wide an audience as possible. Plus, I get a fat check every time O’Reilly sells the translation rights.

The new languages will include Australian, l337 (“Leet”), Jive, Ebonics, Elmer Fudd, Blissymbols, and Esperanto. Here’s a sample before-and-after paragraph:

Isolating the Column

We commonly see queries that defeat indexes or prevent MySQL from using the …

In the first part of this article we examined the types of conflicts and their causes. In this part, we will analyse some of the methods available to deal with conflicts.

Pessimistic locking (or: conflicts won't happen)

Applicability: synchronous clusters with 2pc

We've covered this topic in the previous article, but it's worth repeating. If you use a synchronous cluster, you don't have conflicts. For example, MySQL Cluster ensures consistent data with updates coming from different nodes. However, MySQL Cluster is not a replacement for a MySQL server, and it has severe limitations.

Optimistic locking

Applicability: synchronous clusters without 2pc (Galera)

Conflicting transactions proceed on different nodes with local locking. The last one then …

From my previous posts, we have some numbers (excluding NDB) for the size of MySQL, so what about PostgreSQL? Here, I used PostgreSQL git trunk and classing things in the contrib/ directory as plugins. I put the number of lines of code in the src/backend/storage directory down as storage engines LoC but did not count it as non-kernel code.

This article is the third in a series on data fabric design and introduces the fabric connector service design pattern.  The previous article in this series introduced the transactional data service design pattern, which defines individual data stores and is the building block for data fabrics based on SQL databases.  The fabric connector builds on transactional data services and is another basic building block of fabric architecture.

Description and Responsibilities
Fabric connectors make a collection of DBMS servers look like a single server.  The fabric connector presents what appears to be a data service API to applications.  It routes each request to an appropriate physical …

Teradata results. Funding for DataXu. The chemistry of data. And more.

For 451 Research clients: Oracle launches major update to MySQL open source database bit.ly/TSONAt

— Matt Aslett (@maslett) February 8, 2013

For 451 clients: Analyzing the chemistry of data bit.ly/TSOV2R By @451wendy Treating sensitive data like dangerous chemicals

— Matt Aslett (@maslett) February 8, 2013

Teradata: Q4 net income $112m on revenue up 10% to $740m, FY net income $419m on revenue up 13% to $2.7bn. bit.ly/14FNS8L (PDF)

— Matt …

This article is the second in a series on data fabric design and introduces the transactional data service design pattern.  The previous article in this series introduced data fabrics, which are collections of off-the-shelf DBMS servers that applications can connect to like a single server.  They are implemented from data fabric design patterns, which are reusable arrangements of DBMS servers, replication, and connectivity.  With this article we begin to look at individual design patterns in detail.

Description and Responsibilities
The transactional data service is a basic building block of data fabric architectures.  A transactional data service is a DBMS server that processes transactions submitted by applications and stores data safely.  Transactional data services have the …

Extract from THE SCALE-OUT BLOG by Robert Hodges (CEO, Continuent)http://scale-out-blog.blogspot.com Data management is undergoing a revolution. Many businesses now depend on data sets that vastly exceed the capacity of DBMS servers. Applications operate 24x7 in complex cloud environments using small and relatively unreliable VMs. Managers need to act on new information from those systems in

Data management is undergoing a revolution.  Many businesses now depend on data sets that vastly exceed the capacity of DBMS servers.  Applications operate 24x7 in complex cloud environments using small and relatively unreliable VMs.  Managers need to act on new information from those systems in real-time. Users want constant and speedy access to their data in locations across the planet.

It is tempting to think popular SQL databases like MySQL and PostgreSQL have no place in this new world.  They manage small quantities of data, lack scalability features like parallel query, and have weak availability models.  One reaction is to discard them and adopt alternatives like Cassandra or MongoDB.  Yet open source SQL databases have tremendous strengths:  simplicity, robust transaction support, lightning fast operation, flexible APIs, and broad communities of users familiar with their operation.  The …

Postgres XC explained  Users demand faster processing and as the processing and reports get faster so do the expectation for even faster performance and scalability. Now days its unthinkable not to deliver the performance  and availability.
All of those challenges require a constant search/development of new and improves solutions. Enter Postgres XC just when you were thinking that RDBMS is dead it comes back with the vengeance. So what is exactly Postgres XC and why should anyone care? 
Postgres XC shares a common name with the Postgres RDBMS but this is where the similarities stop, Postgres is a standalone database, Postgres XC on the other hand is a distributed RDBMS in a "share nothing" configuration. With this publication I'll make an attempt to explain Postgres …

451 Research’s 2013 Database survey is now live at http://bit.ly/451db13 investigating the current use of database technologies, including MySQL, NoSQL and NewSQL, as well as traditional relation and non-relational databases.

The aim of this survey is to identify trends in database usage, as well as changing attitudes to MySQL following its acquisition by Oracle, and the competitive dynamic between MySQL and other databases, including NoSQL and NewSQL technologies.

There are just 15 questions to answer, spread over five pages, and the entire survey should take less than ten minutes to complete.

All individual responses are of course confidential. The results will be published as part of a major research report due during Q2.

The full …