A Story about Teradata, Advanced Architectures, and Distributed Applications

Here is a short story about distributed versus monolithic application design…

Around 1999 Dan Holle and I started thinking about how to better deploy applications that used distributed computing. To be fair… Dan schooled me on his ideas for a better approach. We started with a thing called XML that had not yet released a V1 standard. Application subroutines stored state in XML and persisted the XML the best that we could with the tools at the time.

Around 2002 he and I approached Teradata with some very advanced functionality, and some code, that was built on this distributed foundation… and Dan eventually took a job at Teradata to develop this into one or more products.

Unfortunately, the Teradata product management powers could not see the sense. They were building apps the old way and would continue to do so. Dan was caught up in several years worth of battling over the proper architecture and our real intellectual property, the advanced functionality, was lost in the fray. The product management folks insisted that a monolithic architecture was the right way to go and so it went…

This was an odd battle as you might assume that Teradata was a thought-leader in distributed computing…

As you might guess… Dan eventually left Teradata a little bruised by the battle.

Today we realize that a monolithic application architecture is a poor substitute for a distributed architecture. The concepts we brought to Teradata in 2002 underpin the 12 factor app formulation that is the best practice today (see here).

So I’d like to point out that Dan was right… the Teradata Product Management folks were wrong… and that their old school thinking robbed Teradata of the chance to lead in the same manner that they once led in parallel database computing (today they lead in the market… but not in tech). I’d like to point out the lost opportunity. Note that just recently Teradata acquired some new engineering leadership who understand the distributed approach… so they will likely be ok (although the old dweebs are still there).

I hope that this story provides a reason to pause for all companies that depend on software for differentiation. When the silly dweebs, the product managers and the marketeers, are allowed to exercise authority over the very smart folks… and when the executive management team becomes so divorced from technology that they cannot see this… your company is in trouble. When your technology decisions become more about marketing and not about architecture, your tech company is headed for trouble.

PS

This blog is not really about Teradata. I’m just using this story to make the point. Many of the folks who made Greenplum great were diminished and left. The story repeats over and over.

This is a story about how technology has changed from being the result of organic growth in a company to a process whereby the tech leaders become secondary to the dweebs… then they leave… and so companies have to buy new tech from the start-up community. This process forces fundamental technology through a filter devised by venture capitalists… and often fundamental technology is difficult to monetize… or the monetization process fails despite sound underlying tech.

It is a story that points out one of the lessons from Apple, Google, and other serially successful tech companies. Executive leadership has to stay in touch with the smart folks… with the geeks… with the technological possibilities rather than with the technological  “as is”.

Finally, note that Teradata might have asked me to join back up in 2002… and they did not. So not all of their decisions then were mistaken.

3 thoughts on “A Story about Teradata, Advanced Architectures, and Distributed Applications

  1. Thanks Robb. Very interesting to read thefirst-hand account of what happened to Dan and you…

    You are right – this is less about any company per se but more about tech leaders’ ability to embrace the tech shift as needed. As we all know, this is tough to do as hind-sight is always 20:20.

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    • I think that it is about how companies pick tech leaders, Ken. They often place followers in leadership positions and pay them lots of money to be one or two steps behind.

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  2. I have to say WhoWhatWhere (& Fido, the self-learning databot) was way ahead of it’s time. Only now, over a decade later, am I starting to see applications that rival its analytic capabilities & ease of use in the likes of Watson, & Lift Analytics for Retail. Just goes to show, it’s not easy being a trailblazer

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