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Cassandra is fast emerging as one of the key NoSQL databases.  While we often express that the point of NoSQL is to offer more choice than an “RDBMS” hammer for every nail, there are practical reasons why a small number of stack technologies gain dominance and others circle on the sidelines.

• The ability to scale across many nodes
• The ability to scale to many hundreds of

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Ingres

Back from Hiatus - Summary Update 1

GoodData

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KickFire

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The following is a list of interesting DBMS related links for the week:

• Ellison's Impatience Over Sun
• Intel squeezes one million IOPS from desktop
• Is the RDBMS doomed (yada yada yada) ?
• EDS

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I was speaking with Michael Stonebraker this morning.  I mentioned that lately many have been referencing comments he has made over the last couple of years.  And I also mentioned that many had interpreted them as he was implying the RDBMS is “doomed”.  Mike has been saying the same thing for years, but the current NoSQL movement seems to have picked up on this and highlighting one of the RDBMS's own

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There will be plenty of detailed coverage on Exadata V2 so I won’t attempt to replicate that.  However I do have a couple of initial thoughts which I would like to share.  For those who missed it, Oracle has just announced Exadata V2 (which is their pre-built “machine”).  Exadata V1 was built using HP equipment, Exadata V2 is using Sun.  The main addition to Exadata V2 seems to be an extra tier in the memory hierarchy, a flash cache.  Oracle is very quick to point out this is not flash

I haven’t blogged in over a month now.  This is for a number of reasons.  Firstly I have been flat out with various activities.  This included a trip to VLDB in Lyon mid month.  Secondly, a lot of the companies I have spoken with this month aren’t ready to speak publically so hence no blog posts resulting from these sorts of discussions.

However there has been a wiff of a change in the air in terms of focus that is interesting and worth highlighting.  After years of lots of innovation around data analytics, OLTP is starting to make a comeback in terms of reclaiming some of the limelight.  Much more on this between now and the end of the year, but a couple things to watch:

I was fortunate enough to speak with Marcin Zukowski earlier about VectorWise.  If you missed it, VectorWise came out of stealth mode a day or two ago.  The have announced a joint partnership with Ingres and essentially are claiming impressive analytic RDBMS performance gains on conventional hardware.

To start with, a key message that I think needs to be communicated here is that this is not a product announcement.  Ingres and VectorWise have announced a partnership in which they of course plan to build products together, today those products are still in the works.

VectorWise is a spin out of

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I had a quick chat with Michael Widenius today.  He is on vacation so tried to keep the call short.  Essentially spoke about two topics, Oracle & an update on Maria.

The Monty Program has 15 staff now.  Their focus is getting the MariaDB branch of MySQL ready for release, I understand they have a target of next month (August) for this release.  The Maria storage engine has been delayed for the time being with the focus

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

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

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

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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

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,

(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

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

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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

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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 &

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

Oh my. This is just immensely funny & sad at the same time - Amusing Database Videos http://www.bigdatabaselist.com/wiki/Amusing_Database_Videos

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The NoSQL event has triggered a bit of a hard time for the RDBMS the last week.  I won’t add any commentary as this follows what I have been talking about for a while, but here are some of the links.  Most notable is Michael Stonebraker’s post on the ACM site.

• The End of a DBMS Era (Might be Upon Us)

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Todd Hoff has posted a link to a Los Alamos National Lab presentation on Graph Databases.  In this paper they provide a revisit on the classic RDBMS vs Graph database debate.

The Relational Database hasn’t maintained its dominance out of dumb luck.  Instead the RDBMS has consistently outperformed while providing the most general use capability of all the variety of platforms that have been

The last 24 months has seen the introduction of Map/Reduce functionality into the data processing arena in various forms.  Map/Reduce is a framework for developing scalable data processing functionality, and was popularized by Google (see this earlier post).

Pure players like Hadoop are starting to find their own niche, helped by organizations such as Cloudera.  However there has been a number of for & against arguments relating to Map/Reduce functionality inside the database.

These arguments are now really serving a moot point.  Customers have recognized value in Map/Reduce prompting some (b)leading edge database vendors to

A bit of fun for a Sunday.  Below is the list of my top 10 interesting companies in Data Management right now.  Interesting to me means doing new stuff and being somewhat disruptive, or have a “watch and see” quality about them.  Note this is about companies not data management applications. 

While I find a bunch of other data management applications interesting (PNUTS, Cassandra, Redis etc) these aren’t really encapsulated in a company with a go to market strategy.

10gen - They are making interesting noises not sure about delivery yet
Amazon – SimpleDB is neat, but not a grown up data platform yet
Aster Data – Doing funky things with