“As individuals, we are our relationships and our connections to people, and what we do with them,” Guestrin says, perhaps revealing a bit of the graph dataset philosophy.
Since moving to Seattle last August, Guestrin has been talking to GraphLab users, colleagues, and investors about how to push the technology further than it could go as an open source offering from a university, he says.
He has been transitioning his efforts to form a stand-alone company in the last few months.
“GraphLab is my dream,” he says.
Guestrin’s decision to launch a business based on the technology is motivated in part by his desire to make GraphLab sustainable—something he’s not certain it can be solely with support in the open source community.
“There have been other companies that have been able to maintain a self-sustaining, effective effort in the open source community, but also pay the salaries of the people involved,” he says.
The Mozilla Foundation would be one obvious example—albeit a nonprofit one.
“GraphLab, given the level of engagement, the number of people, and the type of engagement—it just can’t be done by a few students in an academic lab,” he says. “We need a larger number of people involved in order to continue to make it valuable and effective.”
He’s aiming for a headcount “in the teens” and has made hires from academia and “from top companies in the Seattle area.” The company is working from incubator space in Fluke Hall on the UW campus.
(The lab in GraphLab, by the way, is for both laboratory, and the Labrador retriever that was Guestrin’s companion when the technology was conceived. “There’s a genesis story for names that may or may not be true,” Guestrin quips.)
Seattle is the right place to build a big data company with heavy academic underpinnings, he says, because of the active connections between entrepreneurs and research at the UW. “That brought me a lot of good mentorship, advice, connections, and collaborations,” he says.
How will he balance academic responsibilities with being a startup CEO? “There’s inspiring examples of how that can be done with Oren Etzioni and Dan Weld and others,” Guestrin says, referring to other UW professor-entrepreneurs.
“Beyond that, Seattle as a whole is an exciting place to be doing this kind of thing,” he says, pointing to the leadership in cloud computing infrastructure from the big three of Amazon, Microsoft, and Google.
Madrona’s McIlwain notes the expertise—commercial and academic—accumulating in Seattle around big data.
“We think there’s these horizontal plays like GraphLab, Context Relevant, and Tableau, but that also all innovative companies need to be data analysis-driven.”
As a commercial enterprise, GraphLab Inc., will work on a broader, more robust platform for analysis of enormous graph datasets, and may provide bespoke solutions for individual customers, Guestrin says. He emphasizes that the company plans to continue to make contributions to the open source community.
One area of innovation in the latest version—Graph Lab 2.2, which the startup plans to introduce to the open source community at a San Francisco workshop in July—integrates ideas developed by one of Guestrin’s students at Carnegie Mellon for running a graph dataset analysis on machines as small as a Mac Mini. The platform can now be scaled from there all the way up to the full horsepower of a cloud computing cluster, depending on the size of the dataset and how fast an answer is needed.
In addition to McIlwain, Greg Papadopoulos of NEA is joining GraphLab’s board. The company also has a technical advisory board including UW computer science chair Hank Levy; Sujal Patel, founder of Isilon Systems; and Chris Stolte, co-founder of Tableau Software.
