Pachyderm, the startup that has built an open source platform for employing containers, such as those made in Docker, for running big data analytics and processing jobs, has raised $2 million in a new round of funding.
The funding, which is Pachyderm’s seed round, comes from a cadre of venture capital firms including Data Collective, Foundation Capital, Blumberg Capital, Susa Ventures, Crunchfund (which, for disclosure’s sake, was founded by TechCrunch founder Michael Arrington), Caffeinated Capital, Soma Capital, and Ace & Company. Also pitching in were angel investors Paul Buchheit, Jonathan Abrams, Avichal Garg, and Jay Jamison.
As I wrote at its launch back in January, Pachyderm is an open source tool that lets programmers run analysis of large amounts of data without writing a line of Java or knowing a thing about how MapReduce works. This purportedly makes big data processing and analytics accessible to a much wider swath of developers than has historically been possible. Pachyderm’s tagline is that it provides “the power of MapReduce without the complexity of Hadoop.” You can read my more in-depth explanation of what that means here.
Pachyderm’s co-founders Joe Doliner and Joey Zwicker said in a phone interview this past week that the new funding will be put toward hiring more engineers and building out new features to accommodate the growing line of customers interested in using Pachyderm’s technology. “We’re really really excited with how much interest there is in this idea. Containers in general have a huge amount of momentum,” Doliner said, adding that in addition to companies, Pachyderm is seeing a notable amount of interest from academic institutions. In the months ahead, he said, Pachyderm plans to build out a GitHub-like web interface that lets people more easily write and share data analysis jobs.