Explosive application growth is forcing organizations to embrace new ways of managing and serving information about users, including metadata, preferences, user state and other data types. Startups and enterprises alike are turning to MongoDB to realize increased agility, time to market and superior user experience.
Challenges
User data is central to a vast array of applications: customer relationship management (CRM) tools, games, mobile apps, identity and access management (IAM) tools, enterprise resource planning (ERP) apps and others. Modern applications must store, track, analyze and serve up various types of user data such as logins, profiles, behavior and real-time attributes.
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Complex User Data Models. Organizations are contending with increasingly complex user models that store new types of data and metadata, like clickthrough behavior and user relationships. Moreover, this data may be spread across multiple backend systems to support disparate applications and user bases.
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Short Development Cycles. User data models need to be updated weekly or monthly to keep pace with business and market developments.
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Real-Time Needs. Applications need to be able to store and serve relevant information to users in real-time to provide a high-quality user experience. For a mobile game, this could be session state and player scores. For a CRM application, this could be recent customer purchasing behavior or web browsing activity.
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Massive User Bases. Modern applications may serve anywhere from hundreds to millions of concurrent users across the globe, creating a challenge of scale.
Relational databases struggle to support massive user bases, leading to poor user experience. The challenges associated with schema changes to accommodate evolving user data models further limit the suitability of relational databases for modern user data management. MongoDB is a NoSQL database that is built to accommodate quick application evolution and massive scale.
MongoDB Solution
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Dynamic Schemas. Whether managing profiles for a social network or for an identity and access management system, MongoDB’s support for dynamic schemas makes it possible to iterate on user data models continuously to reflect changing business and market requirements. NoSQL databases such as MongoDB allow for flexible data models that are easy to work with.
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Rich Querying. A full query language and secondary indexes empower applications to serve the right information to the right users at the right time.
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Real-Time Analytics. MongoDB’s native Map/Reduce and aggregation framework enable applications to provide actionable user data in real-time. For instance, a CRM application for call centers can let a customer service rep know if other customers are experiencing similar issues in real-time.
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Horizontal Scaling. Auto-sharding makes it possible to scale applications horizontally on commodity hardware to accommodate growing user bases and increased throughput. NoSQL databases such as MongoDB are also cloud-native.
Benefits
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Superior User Experience. Providing superior user experience is crucial to earning and maintaining customer loyalty. MongoDB enables organizations to support the performance requirements that users have come to expect.
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Accelerated Time to Market. Rising competitive pressures and demands for constant application iteration make it unacceptable for the database to hinder application development. Users demand new features. MongoDB provides business value by enabling organizations to realize accelerated time to market and time to value.
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Reduced Total Cost of Ownership (TCO). Storing large volumes of data in a relational database is expensive and difficult to manage, given high licensing costs and the need for expensive, scale-up servers and shared storage environments like SANs. MongoDB delivers dramatically reduced TCO through increased developer productivity, the ability to leverage commodity hardware and lower licensing and support fees.
