Big Data is creating new opportunities for organizations to serve customers and markets — while also creating and extracting value — in new ways. MongoDB's NoSQL database provides the foundation for many of these systems, not only as a real-time, operational data store but in offline capacities as well. Traditionally, the work of capturing and analyzing data has required different technologies, different infrastructure and redundant costs. With MongoDB, organizations are serving more data, more users, more insight with greater ease — and creating more value worldwide.
Challenges
Big Data refers to the massive growth in the volume, variety and velocity of data being produced and the set of applications that generate, store, process and monetize this data. While this trend represents a tremendous opportunity for organizations across all industries, delivering on the promise of Big Data is no easy task.
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Massive Data Volumes. Applications can go viral overnight. The database must support rapid spikes in data volume and throughput without downtime, without custom code and without delay.
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Real-Time Demands. Applications should not only be able to capture Big Data, but also to provide analysis in-place, in real-time, without moving the data to separate systems. It is no longer sufficient to conduct batch analytics in offline settings. Lightweight analytics should be delivered to serve content dynamically, enable interactivity and improve user experience.
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Rapid Evolution. Organizations must be agile, able to incorporate new features into applications quickly and easily. Those that can adapt to change more quickly will succeed.
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Flexible Deployment. Organizations should be able to deploy on premise, in the cloud or in hybrid environments so they can benefit from the economics of deployment models best suited to their needs.
Traditional technologies struggle to accommodate the velocity, variety and volume of Big Data. Relational databases were designed for a static data model in which data volumes were small, queries defined upfront and the database lived on a single server in one data center. NoSQL databases such as MongoDB are built for today's applications.
MongoDB Solution
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Dynamic Schemas. Application requirements change quickly. MongoDB's dynamic schema provides a simple way to incorporate changes to the database without affecting existing data or application code, and without incurring downtime.
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Operational Intelligence. MongoDB's native Map/Reduce and aggregation framework enable applications to provide insights in real-time, going beyond the capabilities of batch analytics technologies like Hadoop and traditional BI tools.
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Deployment Flexibility. MongoDB was built for commodity hardware and cloud architectures. Further, data is localized for queries to ensure that performance is robust and predictable regardless of deployment size.
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Simple Scale-Out. Unlike legacy relational technologies, MongoDB is designed to be scaled across commodity server clusters. As data volumes and throughput grow, organizations just add more nodes to their clusters, and MongoDB balances the data seamlessly and automatically in the background.
Benefits
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Deliver Big Data Experiences. Leverage Big Data for new types of applications, features and monetization opportunities. MongoDB delivers superior experiences at any scale, and can provide real-time insight into data trends like user behavior and potential security threats.
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Accelerated Time-to-Market. Users demand new features and applications faster than ever before. MongoDB allows development teams to be agile, keeping users engaged and enthusiastic — and helping businesses gain competitive advantages.
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Lower Costs. New technologies and methods are driving down costs and providing new avenues for organizations to capitalize on their Big Data investments. The MongoDB NoSQL database enables organizations to leverage lower-cost options like commodity servers, cloud computing and agile development, helping them decrease their total cost of ownership while also increasing the value they capture from their data.
Customer Examples
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