Tungsten Replicator 2.0.7 was released today. In addition to a large number of bug fixes, this release adds several improvements for multi-master management, and support for Amazon RDS (as a slave).

While the Release Notes show a long list of improvements, I would like to focus on some of them that improve the handling of multi-master deployments.

When we released version 2.0.6, we added the first revision of the cookbook recipes in the build. That was still a green addition, which caused several bug reports. But since then, we have integrated the cookbook in our internal testing, making these recipes more robust and reliable. We are also planning to improve them and eventually …

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 …

I am very excited and thrilled to use the latest release of MySQL 5.6 in production. This is probably the most notable and innovative release in many years, if not ever.

During the last year, we had the chance to work with many new features and test the fixes to old issues. To be honest, I was expecting to have MySQL 5.6 GA before now, and I even wagered with my colleague Francisco that it would be out before the end of 2012. It was nothing special, just a beer in the Santa Clara Hyatt lounge. Unfortunately for me, MySQL 5.6 is now in GA and given that it happened in 2013, I lost the bet and now have to pay for that beer. But I have also lost the full list of things that we saw as relevant, interesting, or really innovative for MySQL.

So I took a step back, took some time, and reviewed what Oracle delivered in this new MySQL release.

Short premise

Oracle developer teams did great work for …

A few years ago, I used MySQL Sandbox to filter binary logs. While that one was a theoretical case, recently I came across a very practical case where we needed to provision an Oracle database, which is the designated slave of a MySQL master.

In this particular case, we needed to provision the Oracle slave with some auditing features in place. Therefore, mass load functions were not considered. What we needed was the contents of the MySQL database as binary rows i.e. the same format used for row-based replication.

To achieve the purpose as quickly and as painlessly as we could, I thought to employ the services of a MySQL Sandbox. The flow of information would be like this:

1. Install a sandbox, using the same version and character set of the master;
…

My previous writings were mostly teoretical, so I wanted to give a more practical example, showing the actual state of the current code. I also wanted to show how I have tried to make the feature fit well into the existing replication features, without requiring the user to enable lots of options or understand lots of restrictions before being able to use it.

So let us start! We will build the code from lp:~maria-captains/maria/10.0-mdev26, which at the time of writing is at revision knielsen@knielsen-hq.org-20130214134205-403yjqvzva6xk52j.

First, we start a master server on port 3310 and put a bit of data into it:

    server1> use test; …

With data volumes and user populations growing, its no wonder that database performance is a hot topic in developer and DBA circles.  

Its also no surprise that continued performance improvements were one of the top design goals of the new MySQL 5.6 release which was declared GA on February 5th (note: GA means “Generally Available”, not “Gypsy Approved” @mysqlborat)

And the performance gains haven’t disappointed:

- Dimitri Kravtchuk’s Sysbench tests showed MySQL delivering up to 4x higher performance than the previous 5.5 release.

- Mikael Ronstrom’s testing showed up to 4x better scalability as thread counts rose to 48 and 60 …

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 …

Tungsten clusters use the Tungsten Connector to ensure your applications transparently connect to the master. This enables failover and seamless switching of masters for maintenance. However, you can do far more. Tungsten Connector allows you to make better use of hardware by load balancing SQL traffic to slaves. There is also a wealth of configuration settings to help Tungsten Connector manage

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 …