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MetLife is building new products on new technologies thanks to a $300 million investment in new technology and new skills. One of the first products is a MongoDB-based app that puts all of customers’ information in one place

The insurance industry hasn’t always been a beacon of technological innovation. Then again, its major providers haven’t always earmarked $300 million for investments in new technology and new talent like MetLife has. The strategy has already borne its first fruit in the form of a new database system and application that lets the company see everything it knows about a customer in a single place.

How big an undertaking was it? Built atop MongoDB, The Wall brings together data from more than 70 legacy systems and merges it into a single record. It runs across six servers in two data centers and presently stores about 24 terabytes of data. That includes MetLife’s entire U.S. customer base (some 45 million agreements in total), although the goal is to expand it to international customers and multiple languages, as well, and maybe even create a customer-facing version. It updates in near real time, just like the Facebook wall, as new customer data is entered.

Building a production database system on NoSQL technology isn’t commonplace in insurance or other large industries, but it was about the only way to pull this off. Going with the relational model, Hoberman explained, would have meant figuring out a common set of schema across such a wide range of products (insurance products and terms vary from state to state and country to country) that it would have been nearly impossible to actually achieve that coveted 360-degree customer view. MongoDB let Hoberman’s team build some light schema to give the app order, but to be able to take in all the data it had available.

Bill Gurley, partner at Benchmark Capital, leveled a number of serious charges at a ballroom full of New Yorkers this week–the city has yet to produce an iconic venture-backed company, he said. And, he added, people here are more likely to sell early rather than create a true home-run for a venture firm via an IPO.

But DoubleClick co-founder Dwight Merriman disagreed when he heard of Gurley’s assessment of the New York startup scene.

“I think there’s a bias against early exits [in New York],” said Merriman on the sidelines of the conference. Merriman has co-founded three currently private companies based in New York: 10gen, Gilt Groupe and Business Insider. None of these are considering early exits, even though they could be sold, he said.

“I don’t see [early exits] happening” in New York, any more than in Silicon Valley, said Merriman.

Merriman added that several New York companies over the past 12 months raised late-stage venture financings that valued them at more than $500 million, probably as many as there were in Silicon Valley. Besides his own startups, Merriman counted venture-backed New York companies like Tumblr, AppNexus, ZocDoc and Foursquare as those with highest value.

The New York startup and venture scene is growing quickly, he said, and it’s still pretty young, so he isn’t surprised major IPOs haven’t happened yet.

10gen, for its part, has more employees, including engineers, in its New York office than in Palo Alto, Calif., said Merriman.

MongoDB steward 10Gen is trying to squeeze money out of heavy users of the open source NoSQL database, and has set aside almost a petabyte of raw storage to deal with initial demand for a new backup-and-restore service.

Like other companies that shepherd an open source product (Canonical – Ubuntu, Basho – Riak, et cetera), 10Gen has to walk a fine line between introducing features that enterprise users want, while not alienating standard developers of the free version who may feel left out.

The MongoDB Backup Solution, announced Tuesday, is an attempt by the company to walk this tightrope. The technology provides a way of incrementally backing up the database, where previously it was only possible to do full backups and restores via the native mongodump and mongorestore utilities.

Alongside big-city problems like lowering the murder rate, cutting the number of stolen garbage carts may seem like small stakes. But lost garbage carts actually cost Chicago a lot of money and time -- it takes scarce resources to field the complaints, acquire new carts and pay staff to deliver them. What if data analysis could help the city minimize the number of lost carts?

Evaluating garbage cart losses with mapping software and comparing that information to streetlight failures, city staff confirmed what they had suspected: In certain neighborhoods, if the alley lights go down, garbage cart thefts spike. That intelligence gives a new sense of urgency to getting lights repaired.

"Government has been very good at collecting data, but not as good at using the data," says Brett Goldstein, the city of Chicago's CIO. So Chicago is in the process of building a predictive analytics platform that will do more analysis and much more sophisticated analysis. That work is being funded in part through a $1 million grant the city received in March as a runner-up in Bloomberg Philanthropies' Mayors Challenge, a competition to fund innovative ideas in city government.

The city still has far to go in completing the predictive platform. Goldstein has spent the past two years laying a foundation for this analytics work, including hiring experts from the private sector and academia with experience in big data and open source. His team has also created a single database on the MongoDB open source platform, into which data is fed from dozens of legacy IT systems, providing better visibility into municipal operations across departments.