MongoDB Atlas database for government, powered by AWS, offers agencies advanced agility to manage deluge of data

Federal agencies are grappling with an ever-expanding deluge of unstructured data—from text documents and emails to images, videos, surveillance footage, and sensor outputs—critical for everything from national security to public health.

That explosion of unstructured data presents a formidable challenge: how to effectively store, correlate, and analyze such diverse information in combination with structured data in order to make better-informed decisions. The traditional, rigidly structured databases that have long served as the backbone of government data systems are often ill-equipped for this task, highlighting an urgent need for more agile and flexible database platforms.

This necessity is further amplified by the rapid advancements in Artificial Intelligence (AI). As agencies look to leverage AI for real-time decision-making, predictive analytics, and enhanced citizen services, the ability to seamlessly integrate and process vast quantities of varied data becomes paramount. The next generation of database platforms, such as MongoDB Atlas for Government, provides agencies with a powerful set of flexible and cost-effective capabilities designed to handle data complexity and volume at scale.

These insights are central to a new report, “MongoDB Atlas for Government: Creating agility to capture the power of public sector data at scale,” published by Scoop News Group and underwritten by MongoDB and Amazon Web Services (AWS). The report examines the distinct capabilities of modern database solutions and how they can revolutionize federal agencies’ ability to manage and scale their data more effectively.

Gary Taylor, advisory solutions architect at MongoDB, explains in the report, “Traditional relational databases were created in the day when storage was very expensive… In today’s world, storage is not expensive at all. Yet agencies pay a growing cost as system performance degrades, data volumes expand, and data is increasingly distributed across multiple clouds.”

MongoDB’s “document” approach to database development is widely recognized as a preferred platform, “built by developers for developers,” says database industry analyst John Foley in the report. “It’s particularly well suited for agile prototyping and iteration and for getting the project moving forward quickly,” he says.

MongoDB Atlas for Government, powered by AWS, has the added distinction of having achieved FedRAMP Moderate authorization, which streamlines the adoption process for federal agencies by certifying U.S. government security and compliance requirements. Rather than having to stand up, configure and maintain MongoDB instances in-house, agencies can securely deploy, run and scale most of Atlas’ key capabilities as a service in the government cloud.

The report highlights several key advantages agencies can gain by leveraging MongoDB Atlas database capabilities, including:

• Diverse data handling: Unlike SQL databases that require data to fit into predefined rows and columns, MongoDB utilizes a flexible JSON-like document model. This “allows each document to have its own unique structure,” the report notes, making it ideal for the unstructured and semi-structured data overwhelming agencies.
• Agility and Faster Iteration: The schema flexibility means developers can adapt to changing data requirements and prototype applications more rapidly, without disruptive “alter table” statements common in relational systems. “As Mongo’s people like to say, ‘MongoDB was built by developers, for developers.’ That’s one of the reasons sometimes businesspeople may not fully appreciate the platform, because it’s geared to the developers,” observes John Foley, an industry analyst and editor of the Cloud Database Report, quoted in the analysis.
• Scalability: MongoDB is architected for horizontal scalability (sharding), enabling agencies to easily distribute data across multiple servers to handle growing workloads. This is a more cost-effective and efficient approach than the vertical scaling often required by legacy systems.
• AI Readiness: Crucially for the AI era, the report emphasizes MongoDB Atlas’s built-in vector search capabilities. These enable organizations to efficiently store, index, and query vector embeddings alongside traditional data, essential for AI applications that process unstructured data like text, images, and audio to derive insights.

The report further details MongoDB’s multi-modal advantages, its cloud-native architecture on AWS, and features like Queryable Encryption for enhanced data security. It underscores that by adopting such modern platforms, federal agencies are better equipped to manage the current data deluge and unlock its immense potential, driving innovation and improving mission outcomes in an increasingly AI-driven world.

Download the full report.

This article was produced by Scoop News Group for FedScoop and sponsored by MongoDB and AWS.