MongoDBKatie PalmerAnnouncement
Innovating with MongoDB | Customer Successes, October 2025
Summary
Enterprise organizations are modernizing legacy monoliths, mainframes, and relational databases to improve scalability and system performance. MongoDB launched its Application Modernization Platform, an AI-powered program combining artificial intelligence tooling with migration methodologies. Using these capabilities, Wells Fargo implemented an operational data store to serve 40 percent of external vendor traffic with sub-second response times across more than 7 million transactions. CSX utilized MongoDB Atlas on Azure alongside Cluster-to-Cluster Sync to complete a cloud migration within hours while sustaining continuous operations. Additionally, Intellect Design reduced onboarding workflow times by 85 percent, and Deutsche Telekom scaled daily customer interactions from under 50,000 to approximately 1.5 million.
Context
Enterprises struggle with legacy monoliths, mainframes, rigid relational databases, technical debt, and batch processing delays that hinder scalability, developer productivity, and real-time user experiences.
Approach / What changed
Organizations adopted MongoDB Atlas and the AI-powered Application Modernization Platform (AMP), implementing operational data stores, microservices, internal developer platforms, and Cluster-to-Cluster Sync for cloud migration and data unification.
Takeaways
Wells Fargo built a MongoDB operational data store that shifted its architecture toward microservices, handling over 7 million transactions with sub-second latency.
CSX migrated its near real-time operations platform to MongoDB Atlas on Azure in a few hours using Cluster-to-Cluster Sync to preserve 24/7 availability.
Deutsche Telekom incorporated MongoDB Atlas into its Internal Developer Platform, increasing daily digital customer interactions from under 50,000 to approximately 1.5 million.
Source and freshness
- Source
- mongodb.com
- Published
- Added to Yomu
- Last updated
Summaries are generated from the original by a language model. Check the original before relying on it.
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