Modern data needs a modern database

MongoDB: The Modern Alternative That Outperforms Relational

The Path to Innovation

The data that powers modern applications comes in all shapes and sizes. When traditional relational databases struggle with large volumes of unstructured data, incomplete JSON implementations, and clunky horizontal scaling, innovation suffers. True innovation requires a modern, AI-ready database.

Embrace Flexible Data Models and Simplify Relationships (Without Complex JOINs)

MongoDB's document model naturally supports unstructured and dynamic data, simplifying schema design. By embedding or referencing related data in documents for nested data or one-to-many relationships, you reduce the need for complex JOINs common in SQL. Plus, schema validation ensures necessary structure and enforcement.

Unlock Unmatched Performance, Scalability and Cost Efficiency for Any Workload

MongoDB efficiently handles massive data sets and high traffic with built-in horizontal scaling (via native sharding) and read replicas. Experience rapid data retrieval and lower infrastructure costs compared with a variety of SQL systems.

Accelerate Developer Velocity and Build Modern Applications Faster

Store language-native objects directly, reducing the need for ORMs. Simplify data aggregation with an intuitive pipeline framework. MongoDB natively supports vector search and integrates diverse data types—ideal for AI/ML and microservices. Avoid the complexity and cost of caching or intermediate transformation layers. MongoDB is easier for developers to learn and use, speeding up development cycles.

Companies choose MongoDB over relational

50%Effort saved in migration process

2 minsTime reduction from over 1 hour

“The whole migration was very fast. With Relational Migrator, I would say we saved 50% of our effort."

Neha Yadav
Lead Engineer, Nationwide

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50%Effort saved in migration process

2 minsTime reduction from over 1 hour

“The whole migration was very fast. With Relational Migrator, I would say we saved 50% of our effort."

Neha Yadav
Lead Engineer, Nationwide

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7M+Sub-second service for transactions

40%External traffic served with ODS

"We built an operational data store (ODS) on MongoDB to resolve [technical debt, high costs, skill shortages, and slow changes].”

Ram Vemana
Head of Credit Card & Merchant Data, Wells Fargo

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10xPerformance throughput increase

“We can process 10 times more throughput with MongoDB Atlas than we could on-premises, and we’ve got room to handle even higher capacity.”

Eric Lutts
Senior Director of Database Engineering, Radial

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0Downtime

300Database requests/sec.

“One of the things that I enjoy from Atlas the most is all the metrics. It’s extremely easy just to go to the dashboard and know exactly what the pattern is on each chart, and we have never experienced a performance issue with the server."

Vladimir Carballo
Principal Software Engineer, The Knot Worldwide

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Why MongoDB for your next application

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