MongoDB Atlas for Government is a dedicated environment for government needs that will allow agencies to build and iterate faster all in a FedRAMP Ready environment.
Powering mission-critical applications and systems for all sectors
National, Regional, and Local Governments
National, regional, and local governments are facing pressing challenges with rising costs, changing regulations, and complex technological demands. The traditional systems currently in place are not only expensive, but improperly equipped to handle the industry’s twenty-first century needs for scale, cost efficiency, and flexibility.
MongoDB is built to meet these unique demands through secure, cost-efficient, and scalable solutions that help governments improve the welfare of their citizens.
Education
Educational institutions face complex challenges around providing continuous learning and teaching with limited resources. Leaders are focused on delivering efficient, expansive and highly accessible services that improve student and staff retention.
MongoDB is built to help meet these demands by providing intuitive and cost-effective solutions in a secure environment and within budget.
Defense and Intelligence
The Defense and Intelligence communities face unique challenges to accomplish complex missions. The rise of data in everything we do – from training to combat – necessitates a database that can handle large volumes, rapid scale, and complex data sets.
MongoDB is designed to meet these unique demands through secure, cost-efficient, and scalable solutions.
Solutions that meet your different needs
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MongoDB Atlas for Government
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MongoDB Atlas
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Enterprise Advanced
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DISA STIG for Cybersecurity
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Public Sector resources
Take a look at the below resources to find out more.
Webinars
White Papers
Guides
Blog
Healthcare's Interoperability Problem is Forcing IT Modernization
This session from our Healthcare IT Day for Public Sector looks into the state of the healthcare industry the interoperability standards that the healthcare industry demands.
Data Modeling for The Modern Healthcare Agency
Design for the most common data modeling patterns in healthcare with an operational data model that is easier-to-use, transactional, and higher performing than relational DBs.
Cloud Data Strategy for Public Sector
Learn how cloud-based patient medical and billing data are far more accessible, agile, and cost efficient than data stored locally, enabling superior interoperability and collaboration.
Public Sector success stories
Leading organizations around the world are tapping MongoDB to help them serve their citizens and adapt to the unpredictable.
The Department for Work and Pensions (DWP) is the largest department in the UK government and is responsible for distributing £191bn in welfare, pensions and child maintenance. The Universal Credit programme experienced an enormous increase in demand overnight as the COVID-19 pandemic hit. It left millions unable to work or unemployed. The system had to stay online to protect the most vulnerable citizens, yet it would need to be refined and re-scaled once again. The concern was that with traffic at more than 10 times the usual volume, the system might fail. DWP Digital worked with MongoDB to scale and maintain online services.
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As a public initiative supported by funding from the US Department of Energy, the Materials Project (MP) at Lawrence Berkeley National Laboratory aims to remove guesswork from materials design. The Materials Project generates a lot of data with everything designed around one or more MongoDB databases.
Read customer story →
The Department for Work and Pensions (DWP) is the largest department in the UK government and is responsible for distributing £191bn in welfare, pensions and child maintenance. The Universal Credit programme experienced an enormous increase in demand overnight as the COVID-19 pandemic hit. It left millions unable to work or unemployed. The system had to stay online to protect the most vulnerable citizens, yet it would need to be refined and re-scaled once again. The concern was that with traffic at more than 10 times the usual volume, the system might fail. DWP Digital worked with MongoDB to scale and maintain online services.
Read customer story →
As a public initiative supported by funding from the US Department of Energy, the Materials Project (MP) at Lawrence Berkeley National Laboratory aims to remove guesswork from materials design. The Materials Project generates a lot of data with everything designed around one or more MongoDB databases.
Read customer story →
Like any ancient city, Rome has modern needs to transform, not least because more than four million citizens, students, and tourists live, learn, and explore in this bustling, complex place. It all puts pressure on the hundreds of services that keep the city moving every day. Run by Roma Capitale— the local government body — these services and systems needed to evolve to turn the ancient city into a smart city. They looked to MongoDB and set about building a magical mix of data: a single view of all from different sources and all in different forms.
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When schools went into shutdown during Covid-19, Sanoma Learning and MongoDB Atlas kept teaching as classes went virtual, supporting growth to 12 Million exercises daily. Sanoma Learning had to replace a relational database and move to MongoDB Atlas to meet their needs with the performance, scalability and accessibility they required.
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Starting small can lead to startling results – one person, one laptop, and MongoDB’s technology jumpstarted a project that, with other people joining in, went from prototype to one of the nation’s pioneering projects to analyze and act on municipal data in real time. Called WindyGrid, this system is an intelligent operations platform built on MongoDB. With MongoDB, WindyGrid created a central nervous system for Chicago, helping improve services, cut costs, and create a more liveable city.
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When the Collaborative Research Centre at Germany’s University of Bremen started to plan its data infrastructure in 2014, it first looked at standard structured databases. However, the centre’s researchers quickly realized the data sets they would be working with were extremely heterogeneous – and thus were better suited to unstructured database techniques. MongoDB was a good fit to handle this sort of data at scale, so the centre started to build its testing process around it.
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