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October 31, 2013

Teradata CEO Downplays Big Data in Revenue Slowdown

Isaac Lopez

Teradata CEO Mike Koehler downplayed the role that big data technologies such as Hadoop may have had in the company’s revenue slowdown over the last couple of years. The CEO pointed to projects having moved out to 2014 as a key reason for the disappointing year.

Earlier this year the company put out an earnings warning, which prompted speculation that the rising tide of big data technologies, including Hadoop and NoSQL databases like MongoDB, Cassandra, CouchDB and others were putting the pinch on the old guard.

“We are aware of the speculation that new and lower cost technology offerings are impacting Teradata’s revenue growth,” said Koehler on a conference call to discuss third quarter results. “We believe it is a factor, but a small factor. When costs become a top priority in corporations, many of our customers invest more time and resources to optimize their current analytic environments and also evaluate potentially lower cost alternatives.”

Koehler said that while Hadoop is being used by Teradata customers, the workloads are different. “Hadoop does not address the mission critical complex business analytic workloads which Teradata provides to our customers and excels at,” said the CEO. “Based on the work we are doing with many of our largest customers, we believe that the likely impact of Hadoop on Teradata is minimal.” Koehler added that, while he expects four to eight percent of Teradata workloads to potentially move to Hadoop in the future, he expects that Teradata still has the potential to grow at a double digit clip.

While it’s normal to be skeptical of Koehler’s claims, there have been some interesting developments that may give some amount of credence to them. At the Strata + Hadoop World conference this week, Facebook analytics boss Ken Rudin admitted that the social network, which had started out eschewing the relational database world in favor of Hadoop, is moving to add more relational database systems into their infrastructure (It’s currently an open question which relational vendor is getting that fat nugget).

“As we start thinking about big data from the perspective of business needs, we’re realizing that Hadoop isn’t always the best tool for everything we need to do, and that using the wrong tool can sometimes be painful,” Rudin told the audience. “In reality, big data should include Hadoop and it should include relational, and it should include any other technology that is suited for the task at hand.”

Additionally, there is a sort of pivot happening in Hadoop circles, where the people who are developing, packaging and selling the technology are talking about Hadoop in new ways – especially with the release of Hadoop 2.0. In an article on ZDNet, Hadoop veteran contributor, Arun Murthy, who is also a co-founder of Hortonworks, has taken to calling Hadoop (and it’s YARN component) a datacenter operating system. “The way we look at it is you’ve got Hadoop, which is going to be a really core part of the enterprise architecture, but it’s also got to play really well with the rest of the ecosystem,” said Murthy.

Hadoop is picking up plenty of steam. In an interview with Enterprise Tech’s Timothy Prickett Morgan, Cloudera bosses told the publication that the most common way that they’re seeing Hadoop being deployed is as (what they’re calling) an enterprise data hub. “The important thing to consider here is that we are seeing enterprises going mainstream with Hadoop, and the most common way we are seeing it used is as this data hub,” Cloudera CEO Tom Reilly told Enterprise Tech. “That is why we have integrated and packaged all of the software to create this one place in the enterprise where data goes first. Once it goes there, it can be pushed out to other operational systems, and with the Impala and search capabilities we have added, business users have exploratory use of that data.”

While it looks like the database lambs and lions (or elephants, and, uh rhinos) will coexist for the foreseeable future, positioning for supremacy within the datacenter will continue to be a thing. We’ll look forward to seeing this all unfold over the coming months, and years.

Related items:

Big Hadoop Shops Are on a Hockey Stick Growth Curve

Rudin: Big Data is More Than Hadoop 

Hadoop Version 2: One Step Closer to the Big Data Goal