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If you didn’t think Big Data is big with venture capital, then consider the $6.5 million that three-year-old startup 10Gen collected recently from Sequoia Capital, Flybridge Capital Partners, and Union Square Ventures.
10Gen is the maker of MongoDB, a NoSQL database system suitable for sorting and manipulating data in large Web site applications or cloud settings. CEO Dwight Merriman is a former founder and CTO of DoubleClick, the online advertising system sold to Google in 2007 for $3.7 billion.
10Gen has already had three rounds of funding in quick succession, which yielded $1.5 million in the first, $3.4 million in the second, and now $6.5 million for a total of $11.4 million. The venture firms seem eager to support a early-stage company with promising leadership that claims to be able to manage big data.
Merriman, normally found in New York, where DoubleClick originated, paused from making the early rounds at 10Gen’s recent event in Mountain View, Calif., to talk about the money. “The investors know this space is growing fast. They want us to invest more in database research and develop,” he said. The likely means his 20-person company is headed toward 30 employees in its offices in Redwood Shores, Calif., and New York.
Merriman is one of the believers in NoSQL systems as a future enterprise technology, taking its place alongside relational databases, not replacing them. They are much better than relational, however, “for storing online data, writing the data to storage all the time” instead of siphoning off a few key relational rows.
10Gen only produces MongoDB as open source code now and offers technical support, training, and consulting services. But Merriman says the day will come when the system is big enough and well established enough for 10G to add some for-pay products. But his focus now is making “a really good core product” out of the document-oriented system.
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By document-oriented, he doesn’t mean the database stores only documents. On the contrary, it’s more likely storing groups of software objects that might not appear related, but are. When a document is broken down into different pieces of text and images, they are stored in such a system, but many other unstructured data objects find their way into MongoDB as well, say all the information collected on a customer during one visit to the company’s Web site.
Merriman freely concedes that MongoDB and other NoSQL systems, such as Cassandra or CouchDB, are not necessarily good at capturing long-lived, complex transactions. Relational databases are still good for that. But MongoDB can rapidly scale out to capture really large data sets, sort them, report on them, analyze them.
“They’re good at archival. They’re good at event logging,” he noted, then performing analysis on the large data sets to learn things from a disparate set of events.
And they’re catching on fast. “Look at this event,” he noted, “gesturing to the halls filling with MongoDB developers at the MongoSV for Silicon Valley event held Dec. 3. His last West Coast conference was at the former Federal Reserve Building in San Francisco’s financial district, a much smaller venue, and about 200 showed. Now he was hosting 500 attendees in a building meant to stage developer conferences, with video piped from room to room. “This facility is great,” he said, and he thinks the future for NoSQL systems looks bright as well.