Speaking of conferences, in general, and OpenSQLCamps in particular, there is one a week from now, and I will be speaking! It is organized as a single room track at Froscon, Germany, by Felix Schupp (Blackray/Softmethod) and Volker Oboda (Primebase). The content is mostly a collection of database related talks originally submitted via the main Froscon call for papers. (In other words, unlike many previous camps, the schedule is all set.)

I'm a little excited about this one, because for the first time in my career as speaker I will be giving the keynote. The title of my talk is

How I learned to use SQL and how I learned not to use it

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Conor O'Mahony over at IBM wrote a good post on a favorite topic of mine “The Future of the NoSQL, SQL, and RDBMS Markets”.  If this is of interest to you then I suggest you read his original post.  I replied in the comments but thought I would also repost my reply here.

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Hi Connor, I wish it was as simple as SQL & RDBMS is good for this and NoSQL is good for that.  For me at least, the waters are much muddier than that.

The benefit of SQL & RDBMS is that its general purpose nature has meant it can be applied to a lot of problems, and because of its …

We’ve written about how a bad economy is indeed good for open source software. We’ve also recognized that with open source software’s maturity and place at the enterprise software table, a bad economy can be a double-edged sword for open source since the failure or fade of large enterprise customers, say big banks, hurts open source vendors right alongside traditional software providers.

What is interesting is that after a couple of years of economic rebuilding, we’ve seen recently how open source is being driven by innovation, particularly in cloud computing, …

These days products based on the database technologies are getting hatched with the speed of light. From the giants like Oracle and Microsoft to the start-ups, there is an army of products which is growing by the week. It’s become hard to remain abreast of all these technologies, but thanks to blogs, we get the [...]

Supporting successful services on the web means scaling your back-end databases across multiple dimensions. This blog focuses on scaling access methods to your data using SQL and/or NoSQL interfaces.

In Part 1 of the blog series , I discussed scaling database performance using auto-sharding and active/active geographic replication in MySQL Cluster to enable applications to scale both within and across data centers.  

In Part 2, I discussed the need to scale operational agility to keep pace with demand, which includes being able to add capacity and performance to the database, and to evolve the schema – all without downtime.

So in this blog I want …

My friends over at IA Ventures are looking both for an Analyst and for an Associate to their team.  If Big Data, New York and start-ups is in your blood then I can’t think of a better VC to be involved in. 

From the IA blog:

"IA Ventures funds early-stage Big Data companies creating competitive advantage through data and we’re looking for two start-up junkies to join our team – one full-time associate / community manager and one full time analyst. Because there are only four of us (we’re a start-up ourselves, in fact), we’ll need you to help us investigate companies, learn about industries, develop investment theses, perform internal operations, organize community events, and work with portfolio companies—basically, you can take on as much …

In life there are really two major types of data analytics.  Firstly, we don’t know what we want to know – so we need analytics to tell us what is interesting.  This is broadly called discovery.  Secondly, we already know what we want to know – we just need analytics to tell us this information, often repeatedly and as quickly as possible.  This is called anything from reporting or dashboarding through more general data transformation and so on.

Typically we are using the same techniques to achieve this.  We shove lots of data into a repository of some from (SQL, MPP SQL, NoSQL, HDFS etc) then run queries/ jobs/ processes across that data to retrieve the information we care about.  

Now this makes sense for data discovery.  If we don’t know what we want to know, having lots of data in a big pile that we can slice and dice in interesting ways is good.   But when we already know what …

It is a constant, yet interesting debate in the world of big data.  What scales best?  OldSQL, NoSQL, NewSQL?

I have a longer post coming on this soon.  But for now, let me make the following comments.  Generally, most data technologies can be made to scale - somehow.  Scaling up tends not to be too much of an issue, scaling out is where the difficulties begin.  Yet, most data technologies can be scaled in one form or another to meet a data challenge even if the result isn’t pretty. 

What is best?  Well that comes down to the resulting complexity, cost, performance and other trade-offs.  Trade-offs are key as there are almost always significant concessions to be made as you scale up.

A recent example of mine, I was looking at scalability aspects of MySQL.  In particular, MySQL Cluster.  It is …

I found myself reading NoSQL is a Premature Optimization a few minutes ago and threw up in my mouth a little. That article is so far off base that I’m not even sure where to start, so I guess I’ll go in order.

In fact, I would argue that starting with NoSQL because you think you might someday have enough traffic and scale to warrant it is a premature optimization, and as such, should be avoided by smaller and even medium sized organizations.  You will have plenty of time to switch to NoSQL as and if it becomes helpful.  Until that time, NoSQL is an expensive distraction you don’t need.

Uhm… WHAT?!

I’ve spent more than a few years using MySQL and have been using some NoSQL systems for the last year or so in a fairly busy environment. And scaling is only one of the considerations that factor into …

Memcached access to MySQL Cluster

As described in an earlier post Memcached is an extremely popular caching layer used in most big web properties and we’re adding the ability to access MySQL Cluster directly using the familiar Memcached key-value/NoSQL API without needing to go through the MySQL Server. There is a huge amount of flexibility built into this solution – including:

• Decide what data should be held only in the Memcached server; what should be written straight through to MySQL Cluster and then discarded  and what data should be cached in Memcached but persisted in MySQL Cluster
• Where data is held both in Cluster and the Memcached server, they …