The NoSQL movement has been gaining some steam lately, with discussion forums and mailing lists popping up all around the web.  Despite having a career that has been centered on the RDBMS, I have made no secret that I think we have gone too far down with our RDBMS for everything mindset.  I think we need to add a few more tools back into our data toolbox. 

Today, 99.5% of new data centric developments started will use a RDBMS by default.  Maybe .5 of a % will consider using something as obtuse as a NoSQL platform.  By experience I know the majority of people discussing NoSQL platforms today are web developers.  In fact there is almost a sense of trying to trying to keep this under the radar of DBAs.  If we don’t talk to the DBAs about this stuff then they won’t bother us with all that …

This post was a bit of a test to see if I could write a serious post about a database platform called Hamster.  I think I just made it :)

With all the noise over key/value stores recently, we should keep in mind that this technology isn’t exactly new.  It is being applied to new problems, but many of the foundations have been around for decades.  Probably the oldest of them all, Berkley DB came into existence during the mid ‘80’s and now has over 200 million deployments (according to the Oracle web site).

HamsterDB, while not having the same pedigree of Berkley, has been steadily worked on by Christoph Rupp for the last 5 years.  I spoke to Christoph yesterday about his release of a new edition of …

I spoke to Daniel Abadi this morning about his HadoopDB announcement that came out a couple of days back.  I am sure this has been a busy time for Daniel and his team over in Yale as HadoopDB has been getting a lot of interest which I am sure will continue to build.

Some notes from our discussion:

• HadoopDB is primarily focused on high scalability and the required availability at scale.  Daniel questions current MPP’s ability to truly scale past 100 nodes whereas Hadoop has real examples on 3000+ nodes.
• HadoopDB like many MPP analytical database platforms uses shared nothing relational database as processing units. HadoopDB uses Postgres.  Unlike other MPP databases, HadoopDB uses Hadoop as the …

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A while ago, about 16 years ago now, I had a desktop computer.  It wasn’t a PC.  It was an Acorn.  It had an ARM processor in it.  Despite the rest of the world starting going crazy for the new Pentium chip, the Acorn with its ARM processor could run rings about it in terms of computing power.  And it was simple and easy to use, I used to write applications in assembly code for it (and it didn't have a fan!).

Not too long after that Acorn went under, Arm was already off on its own to find a new market.  Its …

Forrester put out its Enterprise Data Management Q2 2009 report a few days ago, you can buy it from Forrester but it also seems to now be available for free from Microsoft here.  I don’t actively seek out these reports as they usually just re-enforce common knowledge (this one was no exception), however as it turned up I managed to find some time on the weekend for a quick read through.

Few surprises in this report, but some key mentions are:

• DBMS market expected to grow 8% annually
• IBM, Microsoft & Oracle own 88% of the DBMS market (by revenue)
• Current market estimated at $27 billion, $32 billion by 2013
• IBM, Ingres, Microsoft, Oracle, PostgreSQL, …

(yeah, this company is going to have to get used to the Austin Powers references.)

Groovy Corp put out a press release last night that starts the official launch of their SQL Switch relational database platform.

I have been speaking with Groovy for a few months, and while the press release is a bit noisy there is actually some interesting stuff in it.

First, an overview

• They are an in memory RDBMS
• They have worked with Intel to architect from the ground up for large multi processor concurrency
• Initially they are launching as a multi-core appliance
• They claim 200,000 sql operations per second from a single box
• They are proprietary (not built on MySQL or any other open source …

Recently on a number of sites the benefits for and against have been debated with, on occasion, these conversations falling into abuse being thrown in both directions.

From a pure technical perspective, the TPC benchmarks make little sense and are probably not relevant to 99% of organizations looking to implement a database technology.  But as a tool for generating visibility, debate and improved public awareness of a vendors technology they still have an impact. 

This is marketing, pure and simple.  Having a great TPC result is akin to an author having a great review on Amazon.  Doesn’t mean it is relevant for you but if faced with a stack of titles you haven’t yet read you’ll probably look more closely at the ones you’ve heard something positive about.

TPC’s are a tool for the marketing department, just the same as any other form of …

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BI/Data Warehousing is an easier market to enter for new database platform vendors.  This is for a few reasons.  Firstly, most BI deployments are custom built projects for each organization.  This means the ability to pick and choose various layers of the stack is much greater. 

Secondly, BI/DW projects success/failure metrics are often tied to database platform driven properties – performance, scalability, load times etc.  The ability to stray outside any existing database platform “standards” to choose a platform that better meets key metrics is more tolerable.

Thirdly, because the ratio of BI to OLTP is low, the associated impact of violating a corporate standard is much lower.  With OLTP …

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It is important to realize that there is less diversity in the enterprise OLTP market than at any point in the last 20 years.  Essentially this market has been boiled down to Oracle, SQL Server & DB2 (with few isolated exceptions).   Most new deployments are typically using one of the first two options.  The lack of diversity has created a stalemate or chicken & egg situation.  Enterprises now only want to install new applications that have been built to support Oracle or SQL Server.  This is …

I have been speaking with a lot or new database vendors over the last 12 months and this has prompted me to revisit a post I wrote mid last year.  The basic premise of this post is that your strategy, and the group of people you’re selling to, largely depends on the market sector you are focusing on (Enterprise OLTP, BI/DW, Cloud & Web 2.0).

A database platform by itself is a largely pointless piece of software.  The only way value is produced from a database platform is through the applications that interact with it.  Therefore the only way to be a successful database platform is by making others successful and motivated to use your platform.

Ok, so as a database platform vendor how do you enter this market then? Well there are a few strategies.  Due to the length of this article I have broken it up into Enterprise OLTP, Enterprise Data Warehousing and Cloud & Web 2.0