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Global Financial Institution

Re-engineering a 40+ billion document search platform

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Summary:

A global financial institution, operating at significant scale across multiple markets. With tens of thousands of employees and vast volumes of transactional data, performance and efficiency are critical to daily operations. At the heart of one of their key services was a document search platform. This system allowed teams to query business critical metadata across billions of records and over time, the system had grown complex.

It supported highly flexible, open-ended searches across more than 1,200 metadata fields. While powerful, this flexibility came at a cost. The platform relied on dozens of indexes to keep up with demand, driving up storage, memory usage, and IOPS. Performance was starting to suffer and costs were rising; the system was also becoming harder to maintain.

The client needed a more efficient way forward and asked gravity9 to help redesign their approach.

Tech Stack:

  • Java Backend: MongoDB Atlas, AWS, Gatling (for load simulation), JMeter (for load testing), NodeJS (for data migration scripts

A global financial institution engaged gravity9 to help modernise a highly complex search platform responsible for querying more than 40 billion documents across over 1,200 metadata fields. As the platform had evolved, performance pressures, rising infrastructure costs, and increasing maintenance complexity made it clear that a more efficient and scalable approach was needed.

gravity9 redesigned the core search architecture to enable a safe transition to MongoDB Atlas Search without disrupting existing services. By introducing a more structured query conversion layer, a scalable migration framework, and support for both legacy and new search methods, the client gained a stronger technical foundation for the future one designed to reduce costs, improve query performance, and scale with confidence.

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