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Innovating At Citigroup With MongoDB

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How does a 200-year old enterprise like Citigroup successfully run the bank while simultaneously staying ahead of the curve and innovating around all the new data coming at them?

According to Mike Simone, who heads up CitiData Platform Engineering at Citigroup, one critical part of the answer is MongoDB.

With the emergence of The Internet of Things and the “new data age,” Simone’s team was being asked to build stacks that could “quickly ingest data and analyze at the speed of thought.” They needed a new approach, one that took them beyond their existing relational database technology to combine structured data with new unstructured data. This was the key to propelling Citi forward: both its 40,000 developers and the business itself.

Initially adopted in a single application area to solve a global replication problem, MongoDB has since become an important part of Citi’s strategic direction, as it builds business apps to handle petabytes of data across the business.

“Because of MongoDB’s architectural affinity to be built as a service, we were able to improve DevOps capability and put more responsibility and power into the hands of developers and architects,” said Simone.

MongoDB-as-a-Service (MDBaaS) now enables developers to provision a three-node MongoDB cluster in 17 minutes (with elastic cloud and horizontal scale capabilities), which, at best, previously would take several days. MongoDB also helped cut application development time from point of concept to production in less than four months.

“Four-month incubation is unprecedented speed to market for a large enterprise,” said Simone, “and we’re doing it without compromising things like security and access approvals in between.”

MongoDB’s deployment model also lowers capital expenditures (CapEx) by enabling Citi to use commodity servers while simultaneously lowering operational expenditures (OpEx), resulting in 60% lower total cost of ownership (TCO).

Among roughly 50 MongoDB applications, Citi uses MongoDB for the following use cases: * Data navigator: an information asset inventory navigator or “card catalog” that enables the browsing, selection and requesting of data from Citi’s Big Data environment for analytics exploration; * Data caching above the relational database; * Operational view consolidation (single view of data)

According to Simone, there’s an evolution happening, as MongoDB is moving to a place where it’s becoming more and more mainstream. Not surprisingly, we happen to agree.


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