The new application, called The Wall, is essentially a way to make the customer service experience more palatable for consumers and to lower the burden of hiring new representatives. Because it’s designed to look and function like Facebook, MetLife CIO and SVP of Regional Application Development Gary Hoberman told me, The Wall means new hires don’t have to be trained on complex enterprise call center software. For customers calling MetLife to discuss a claim or their coverage, it means fewer annoying waits as an agent accesses data from any of dozens of different places.

“Instead of seeing what someone had for dinner, [The Wall is] all a customer’s transactions,” Hoberman said. Claims, records, status, possible cross-sell information (e.g., if someone lives in an apartment and might need renter’s insurance) — it’s all in there. Looking forward, he said, it might even contain other publicly available information from social media and certain mobile apps that would give the company even greater visibility into its customers’ lives.

Up and running in 3 months, on MongoDB

From a business perspective, though, the most-impressive part of The Wall is how quickly it was implemented and what a divergence from classic large-enterprise IT practices it represents. For Hoberman, who spent 16 years at Citi before joining MetLife in mid-2012, the process was eye-opening. If you told someone in the financial services industry that it would take just five days to get servers up and running for the prototype of such a big application, he said, “they’d look at you like you had two heads.”

But that’s exactly what MetLife did. In fact, it had the entire prototype built just two weeks after devising it and the production system up and running in just three months. It came together so fast because of MetLife’s new focus on cutting-edge IT and clear mission to build a useful product rather than, as Hoberman put it, “doing big data for big data’s sake.” The tech team was willingly working nights and weekends and the leadership team was directly involved because everyone understood what a fundamental change the application could have on the business.

“In insurance,” Hoberman said, “… working in months, not years, is really a startup mentality.”

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.

Bringing in new tech, and new blood

This is only a part of what MetLife is doing with new information technologies, though, and only a fraction of what it wants to do. With The Wall, specifically, MetLife Hoberman wants to build next-best action models that will give agents guidance on how to best deal with customers. Elsewhere, the company has already used its new centralized MongoDB system to build models for predicting attrition, and it’s using Hadoop and HBase for some other workloads where they’re a better fit.

It’s all thanks to a company mandate to save $450 million from its bloated technology and operations budget and then invest two-thirds of it back into new technology. “We literally have a $300 million investment to decide what’s going to be the future of MetLife,” Hoberman said. It’s kind of like being in a startup, he added, only with the resources to make sure everything is done right (much like with other large enterprises embracing open source, Hoberman’s team prototyped The Wall using open source MongoDB but brought in 10gen when it came time to build a production system).

It might be easy to mock that statement, except that Hoberman and his peers are putting their money where their mouths are by bringing in new talent, as well. It’s setting up a team in the Research Triangle region of North Carolina and bringing in employees with expertise in areas such as social, mobile and big data. And Hoberman is far less concerned with specific technical skills than he is with motivation.

It’s all about “attitude and aptitude,” he said. “They can learn anything.”

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.

• The fourth quarter of 2012 in cloud
• How search can unlock the power of big data
• Takeaways from the second quarter in cloud and data

The MongoDB Backup Service, now in limited release with general release slated for the summer, lets customers determine how often they want to back up their databases at colocation facilities 10gen uses. If a user wants to back up every six hours, for example, then that user has many options to choose from in the way of restoring a database to a previous state. They can choose the version from six, 12, 18 or 24 hours ago. Restores require two-factor authentication and work across multiple shards. Customers pay only for the amount of backup that they use.

10gen, based in New York and Palo Alto, Calif., expects the service to be a hit not necessarily with big companies but with small and medium-sized businesses. “It allows them to focus on building out applications instead of worry about this operational part of the infrastructure,” said Kelly Stirman, director of product marketing at 10gen. Regardless of company size, the feature could be valuable for anyone working in Mongo with larger data sets.

Beyond that, backing up means users can move data from a production environment into a testing environment to look for issues so their production environment won’t be affected.

While many MongoDB users already back up their databases, the systems are typically homemade, Stirman said. The MongoDB Backup Service, by comparison, is more reliable.

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.

• The fourth quarter of 2012 in cloud
• How devops can reduce cycle times
• A near-term outlook for big data

It worked with Basho, the Cambridge, Mass. company behind both the Riak NoSQL distributed database and RiakCS storage to do the integration work. Both the free Riak and  paid Riak Enterprise versions now run on SoftLayer’s pay-as-you-go infrastructure.

As GigaOM’s Jordan Novet recently reported, Riak is used by companies including Github because it stores, replicates and retrieves data, even when multiple nodes fail.

According to a statement by the two companies, the Riak solution makes it easier and faster for companies to “deploy scalable production-grade systems”at the click of a button.”

In March, Basho made its Riak CS distributed storage available under the Apache 2 license. Late last year, Softlayer worked with 10Gen to put the popular MongoDB database on its infrastructure as an option. It’s clearly filling in its NoSQL check boxes here.

Dallas-based SoftLayer’s been the subject of acquisition rumors lately. IBM is (or was) reportedly interested in buying the company.

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.

• The fourth quarter of 2012 in cloud
• Takeaways from the second quarter in cloud and data
• How devops can reduce cycle times

Structure 2012: Launchpad: Jason Hoffman – Founder and CTO, Joyent, Matt Howard – General Partner, Norwest Venture Partners, Aaref Hilaly – Partner, Sequoia Capital

And the finalists are:

28msec: With offices in Palo Alto and Zurich, this startup aims to streamline the task of writing complex queries against your MongoDB database of choice.

Appscale Systems: This open-source implementation of Google App Engine (GAE) can run on a developer’s laptop, on Amazon Web Services or the Google Compute Engine.

Factor.io; This service lets developers knit together their tools of choice — for source control system, for PaaS, for testing — into a coherent, flexible workflow using an “if-this-then-that” interface.

Metrica: Metrica’s service lets folks use SQL queries against their MongoDB data, cutting the time it takes to create histograms, time series, and scatterplots and other data visualizations.

Saltstack:  This startup tool aims to speed up devops tasks including cloud orchestration or in-house server automation and infrastructure management.

Synapsify:  The company’s text search and analytics capability can help companies find the most important and relevant content for their needs.

Structure is GigaOM’s flagship conference that focuses on the future of cloud computing and internet infrastructure. For the past seven years, it’s convened the most influential speakers, buyers and vendors for two days of discussion, reporting, and debate.

Startups less than 12 months old with innovative technologies in cloud computing, internet infrastructure, or big data applications were eligible to apply for LaunchPad. The finalists will present their business plans on stage at the Structure conference in San Francisco, June 19-20. Follow @GigaOM on Twitter (#structureconf) to keep apprised of new speakers and sessions.

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.

• Takeaways from the second quarter in cloud and data
• PaaS market accelerators, 2012–2013
• Cloud computing infrastructure: 2012 and beyond

According to 10gen CEO Max Schireson, Carey’s presence will be important for the company, which has more than 200 employees and should top 500 in the next couple years. While she helps grow and build the corporate infrastructure in the finance, legal and HR departments,  Schireson can spend more time working directly with customers, partners and products.

Carey told me she’s excited about getting back into a high-growth company, especially one like 10gen that has a disruptive technology and open-source business model. Granted, open-source business models do bring their own unique set of challenges on top of those associated with startup businesses, she noted, but they also open up doors for new business.

“I think 10gen has all the elements there to make that a really good fit for me,” Carey said.

Schireson said Carey’s hire isn’t indicative of a forthcoming 10gen IPO, but that is something on which the company is focused. However, he added, some great companies have went public rather late in their lives, so 10gen isn’t rushing that decision and is instead keeping its attention of product development. The company has raised $81 million in venture capital since launching in 2007.

The addition of Carey is just the latest in a series of executive hires at 10gen that includes a handful of veteran big data and database industry vice presidents, as well as Senior Vice President of Worldwide Sales Phillip Carty.

Despite some criticism of its ability to scale beyond a handful of nodes, MongoDB is easily the most-used NoSQL database around, largely because it’s so easy for even novice NoSQL developers to work with and performs well with smaller data volumes. And the MongoDB ecosystem that 10gen helped catalyze is big, growing and potentially very lucrative. There are a handful of popular cloud services around such as MongoLab and MongoHQ, and Rackspace just bought its way into the mix by acquiring ObjectRocket.

Schireson said 10gen might consider some acquisitions that help advance the company’s MongoDB mission, but isn’t really looking at buying its way into the position of a one-stop NoSQL shop right now.

“Right now we’re 100 percent focused on MongoDB,” he said. “Everything we do is somehow related to that.”

This story was updated at 9:22 a.m. to correct the amount of venture capital 10gen has raised to $81 million from $86 million. The company changed the official amount between the time this post was written and the time of its publication.

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.

• The fourth quarter of 2012 in cloud
• How devops can reduce cycle times
• AWS Storage Gateway jolts cloud-storage ecosystem

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.

• Infrastructure Q1: IaaS Comes Down to Earth; Big Data Takes Flight
• Infrastructure Q1: Cloud and big data woo enterprises
• Infrastructure Q2: Big data and PaaS gain more momentum

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.

• A near-term outlook for big data
• 2012: The Hadoop infrastructure market booms
• Defining Hadoop: the Players, Technologies and Challenges of 2011

Drawn to Scale’s flagship product, called Spire, is a distributed data platform that’s built atop an optimized version of the Hadoop-based HBase database. HBase is what lets Spire scale cheaply and easily across. Its fully distributed index is what lets Spire read and write data at speeds that other approaches to scaling databases (e.g., sharding) can’t handle while maintaining the ability to handle rich queries.

To date, the company has been focused on letting users run massive SQL databases, but it has finally completed a lengthy process of rewriting parts of MongoDB to work with Spire, Founder and CEO Bradford Stephens (who’ll be participating in our Structure: Data event this week in New York) told me. The company had been keeping the work under tight wraps “because we didn’t know how long it was going to take to build,” he added.

“Our big vision for the market is providing people with a universal data platform,” Stephens said. After SQL — which accounts for the vast majority of databases in existence — MongoDB is a logical next step (although Spire also supports queries using Hadoop MapReduce). It’s the most-widely used NoSQL database by a longshot, but although many users love its functionality and tooling, the database is notoriously poor at scaling to meet the demands of big data or high performance.

“You just sort of top out once you max out the memory,” Stephens explained, adding that MongoDB often starts getting inefficient as it’s forced to scale across 50 or 10 servers. “[T]hat’s where we start getting efficient.”

Now, without changing a single line of code, he claims, MongoDB users can import their data onto Spire and start handing 200-plus terabytes with ease. Of course, he noted, this doesn’t mean MongoDB users will abandon the database entirely. It might be they keep it for running applications that don’t require it to scale beyond a single server, and then use Spire to store big data for analytical purposes.

Initially, Spire will just support data importation and the basic CRUD (create, read, update, delete) functions of MongoDB, Stephens said. Later this year, assuming users want it, Drawn to Scale will implement MongoDB’s native MapReduce functionality as well as its management features.

As data volumes and data stores continue to proliferate, though, Drawn to Scale isn’t the only startup trying to provide a one-stop shop experience. At least for analytics, Citus Data is building a Postgres-based database capable of analyzing SQL, Hadoop and MongoDB data, although each data store remains external. And there’s a whole group of companies merging SQL and Hadoop for analytic workloads that might be wise to consider supporting operational data stores such as MongoDB, as well.

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.

• A near-term outlook for big data
• Defining Hadoop: the Players, Technologies and Challenges of 2011
• With Scalable Data Stores Around, Is NoSQL a Non-Starter?

10gen had greater business adoption in mind last year when it raised $42 million and vowed to focus on research and development to improve MongoDB. Now, around 60 percent of customers are enterprises, said Kelly Stirman, the company’s direct of product marketing.

Once signed up for the MongoDB Enterprise software, customers can use their own on-premise hardware to run an extension of the MongoDB Monitoring Service to track MongoDB deployments with more than 100 metrics and receive alerts. MongoDB Enterprise comes certified for deployment on several operating systems. It also supports the Kerberos authentication protocol, which is popular among insurance companies and banks, and can hook in to customers’ existing monitoring services, such as Nagios. And it introduces roles for giving certain abilities to certain database users.

New features in the MongoDB 2.4 release available to all users include full-text search for querying the database, an option to evenly shard data across machines, more accurate measurements of the distance between locations, the ability to count items in a database 20 times faster than before and the ability to maintain and query leaderboards of, say, the top 50 scorers in a baseball league.

The NoSQL database market is crowded, and differentiation is important. That’s why it’s a good thing 10gen, which is based in New York and Palo Alto, Calif.-and has other offices in Australia, England, Ireland and Spain, will increase its headcount by 75 percent in the next year, Stirman said. The time between product releases is getting shorter and shorter, he said, which means that still more improvements could be just a few months away.

Feature image courtesy of Flickr user junyaogura.

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.

• The fourth quarter of 2012 in cloud
• How devops can reduce cycle times
• A near-term outlook for big data

Chris Lalonde, co-founder CEO of ObjectRocket

The deal, the terms were not disclosed, shows that major cloud infrastructure providers need to offer an array of database options — Rackspace already offers MySQL but Amazon Web Services offers a full slate of databases and managed databases. In December, Softlayer launched hosted MongoDB as a service it developed with 10gen.

“Mongo is breaking away from the pack and our customers are asking for it,” said Pat Matthews, SVP of corporate development for Rackspace, San Antonio, Texas. He said the company could have built its own version of the open-source database or partnered with a MongoDB provider — but was impressed with the expertise of the ObjectRocket co-founders Chris Lalonde, Erik Beebe and Kenny Gorman who between them spent years at Ebay, Paypal, Shutterfly and AOL.

ObjectRocket characterizes its offering as MongoDB as a service, meaning that users don’t have to sweat a lot of the set-up nitty gritty. It competes with rivals like MongoHQ and MongoLab.

“The primary difference between us and other database-as-a-service companies is we built out our cloud rather than layer on top of general platforms,” Lalonde said in an interview. “We built a cloud platform from the ground up specifically for MongoDB, we went to Equinix and did our own hardware platform and tuned the OS and the rest of the stack for Mongo in a way that enables us to get great performance and also have a more highly available system.”

Of course that means integrating it into the Rackspace platform will take time, which is fine with Rackspace, according to Matthews. “The offering as it stands will exist for a while till we can figure out the best ways to integrate it. We will maintain or improve performance and we won’t rush to integrate it at the expense of what we have now.”

Critics could argue that Rackspace is late to this party given the database options Amazon Web Services has, but then again, we’re still pretty early in the cloud deployment game.

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.

• The fourth quarter of 2012 in cloud
• Takeaways from the second quarter in cloud and data
• Infrastructure Q4: Big data gets bigger and SaaS startups shine