Yesterday we ran a webinar discussing the demands of next generation web services and how blending the best of relational and NoSQL technologies enables developers and architects to deliver the agility, performance and availability needed to be successful.

Attendees posted a number of great questions to the MySQL developers, serving to provide additional insights into areas like auto-sharding and cross-shard JOINs, replication, performance, client libraries, etc. So I thought it would be useful to post those below, for the benefit of those unable to attend the webinar.

Before getting to the Q&A, there are a couple of other resources that maybe useful to those looking at NoSQL capabilities within MySQL:

- On-Demand webinar

- …

So yesterday I introduced the newly committed HTTP JSON key-value interface in Drizzle. The next step of course is to create some simple application that would use this to store data, this serves both as an example use case as well as for myself to get the feeling for whether this makes sense as a programming paradigm.

Personally, I have been a fan of the schemaless key-value approach ever since I graduated university and started doing projects with dozens of tables and hundreds of columns in total. Especially in small projects I always found the array structures in languages like PHP and Perl and Python to be very flexible to develop with. As I was developing and realized I need a new variable or new data field somewhere, it was straightforward to just toss a new key-value into the array and continue with writing code. No need …

tldr; A single MySQL Cluster prioritises Consistency in Network partition events. Asynchronously replicating MySQL Clusters prioritise Availability in Network partition events.

I was recently asked about the relationship between MySQL Cluster and the CAP theorem. The CAP theorem is often described as a pick two out of three problem, such as choosing from good, cheap, fast. You can have any two, but you can't have all three. For CAP the three qualities are 'Consistency', 'Availability' and 'Partition tolerance'. CAP states that in a system with data replicated over a network only two of these three qualities can be maintained at once, so which two does MySQL Cluster provide?

Standard 'my interpretation of CAP' section

Everyone who discusses CAP like to rehash it, and I'm no exception. …

A week ago I again had the pleasure to give a guest lecture at Tampere University of Technology. I've visited them the first time when I worked as MySQL pre-sales in Sun.

To be trendy, I of course had to talk about the cloud. It turns out every section has the subtitle "...and why it is more difficult for databases". I also rightfully claim to have invented the NoSQL key-value development model in 2005.

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Read the original article at A handy guide for PHP and MongoDB Web Development

What makes a beginner’s guide handy is when it speaks to your intuition. It anticipates the burning questions that follow from a newbie trying to grasp new concepts and it quickly answers them. PHP and MongoDB Web Development – Beginner’s Guide is one such guide.

I hadn’t heard of Packt Publishing or Rubayeet Islam before picking up this title and I must say I’m impressed. Based in Birmingham, with offices in Mumbai, part of Packt’s business model is to give part of the royalties earned from its books to the open …

It seems that our friends at Oracle have been pretty busy with the GA release of MySQL Cluster 7.2.

This is not just old wine in new bottles.

While it may be a dot release, it does appear to be a more significant step forward than a dot release would imply.

First off, we are very excited to announce that the Severalnines Cluster Configurator now includes support for 7.2 GA.

As the title of this blog suggests, it is possible, as we have experienced, to deploy 7.2 GA in 288 seconds, i.e. just a few minutes. This was done on m1.large instances on Amazon. We have published a quick how-to deployment guide for Amazon here: http://support.severalnines.com/entries/20916823-installing-on-amazon-ec2.

…

As always, I am a little late, but I want to jump on the bandwagon and mention the recent MySQL Cluster milestone of passing 1 billion queries per minute. Apart from echoing the arbitrarily large ransom demand of Dr Evil, what does this mean?

Obviously 1 billion is only of interest to us humans as we generally happen to have 10 fingers, and seem to name multiples in steps of 10^3 for some reason. Each processor involved in this benchmark is clocked at several billion cycles per second, so a single billion is not so vast or fast.

Measuring over a minute also feels unnatural for a computer performance benchmark - we are used to lots of things happening every second! A minute is a long time in silicon.

What's more, these …

“Legacy MySQL does not scale well on a single node, which forces granular sharding and explicit application code changes to make them sharding-aware and results in low utilization of severs”– Dr. John Busch, Schooner Information Technology A super-set of MySQL suitable for Big Data? On this subject, I have interviewed Dr. John Busch, Founder, Chairman, [...]

Links to performance numbers posted wrt various NoSQL solutions:

A top 20 global website announced they have migrated from MySQL to Redis. There will be a keynote and everything. It doesn't say how big the Redis Cluster is, but they serve 100M pages / day, and clock 300k Redis queries / second.
https://groups.google.com/forum/?fromgroups#!topic/redis-db/d4QcWV0p-YM

Btw, they mention that MySQL remains as the master data store from which the Redis indexes are generated.
(The reason I don't mention the name of this Redis user is simply I feat my mom is sometimes reading my blog...)

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I've written a few times about database consistency before, mainly in conjunction with NoSQL and the concept of Eventual consistency. Now, I'm about to do an update on the subject, as I have come to realize a few things.

From an oldtimer like myself, having been an SQL guy for 25 years, I remember Punk-rock and even The Beatles and I having hair growing out of my ears, what can be contributed? Well, let me beging with stating what I mean when I say Database consistency. What I mean is Consistency as the C in ACID (no, we aren't talking drugs here, we are talking databases). Let's see what the online authorative reference work on just about anything on this planet, from the size of J-Lo's feet to the number of Atoms in the universe (those two numbers are quite far apart by the way), Wikipedia: "The consistency property ensures that any transaction will bring the database from one valid state to another. Any data written to the database …