MongoDB: The World’s Leading Modern Data Platform

2 min read Original article ↗

Stream Processing Use Cases

Build scalable event-driven applications that react and respond in near real-time. Atlas Stream Processing unifies the developer experience, enabling you to work with high-velocity data streams from sources like Apache Kafka using the same familiar MongoDB Aggregation Pipeline stages you use for your database.

Operational Use Cases

Optimize write performance with a document data model that maps to your application’s access patterns. Meet a wide range of query requirements via a single query API that supports everything from simple lookups to complex processing pipelines for data analytics and transformations.

Transactional Use Cases

Guarantee millisecond response times at scale with a flexible document data model and rich query capabilities—including secondary indexing, joins, multi-document ACID transactions, and more.

Analytical Use Cases

Unify the core capabilities needed for application-driven analytics with MongoDB Atlas. Perform powerful aggregations and transformations in place and in real time. Leverage optimized indexes, storage, data formats, and an extensive ecosystem of native and integrated analytics services to build smarter applications and achieve real-time business visibility.

Graph Use Cases

Elevate your applications by leveraging MongoDB's native graph data support. Efficiently analyze relationships between data entities in your collections for pattern discovery and intelligent predictions. It’s ideal for powering recommendation systems, fraud detection mechanisms, and managing networks.

Geospatial Use Cases

Easily build applications that leverage geospatial data with MongoDB's native support for GeoJSON and simple coordinate pairs. Harness specialized indexes for blazing-fast queries. It’s your one-stop solution for logistics, location-based services, and spatial analysis.