Image via Wikipedia

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 …

Image by RaghuP via Flickr

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

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

Image via Wikipedia

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)
• Relational databases are dead -- who knew?
• …

Image by ToniVC via Flickr

Image via Wikipedia

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 available.  Many other approaches have been tried, often these have provided better object model integration (OODBMS) or better data model representation.  But when the …

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 introduce such …

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 Map/Reduce
GroovyChannel – Are they nuts, they have to change …

A great post from Jonathan Ellis on "Why you won't be building your killer app on a distributed hash table"

Scroll down to see my comment.  I agree a simple DHT is not a suitable solution for mainstream data management issues, but also I think that there is a gap between RDBMS and DHT.