Quote · The MongoDB Podcast
From Data to Decisions: Powering gen/Agentic AI with Capgemini & MongoDB
Where this was said
Future Partnership Roadmap: Lakehouses, Mainframes & Industrial IoT
At 28:26 · chapter starts 24:28
Apurva asks where the partnership is headed, and Vinay paints an ambitious multi-front roadmap. The first trend: customers are refusing to treat MongoDB as a separate transactional database. A Fortune 500 client migrating to a cloud lakehouse — whether on BigQuery, Azure Fabric, or Azure Data Warehouse — wants MongoDB embedded inside the lakehouse itself, enabling unified data management that spans streaming, object storage, and AI analytics in one estate. [1] — Vinay Makkaji "A Fortune 500 client migrating to a cloud lakehouse isn't treating MongoDB as a separate transactional database — it wants MongoDB embedded…" 24:33 The second major frontier is mainframe and AS400/DB400 modernization: decades of enterprise data locked in EBCDIC encoding can now be migrated to MongoDB using out-of-the-box tooling, unlocking that data for AI workloads. Third, digital manufacturing and industrial IoT — connected vehicles, fleet management, factory of the future — represent a 5-year growth runway beyond oil and gas. Farid adds the strategic dimension: MongoDB is no longer just a database choice for Capgemini; it is a co-investment partner protecting partner margins and accelerating multi-year transformation programs. In some cases, [2] — Farid Mohammad "MongoDB is no longer just a database choice for Capgemini — it's a co-investment partner protecting margins and accelerating multi-year tra…" 28:26 this model has already delivered 30 to 50% improvement in outcomes. The memorable closing line: technology builds capability, but partnerships build outcomes.
Fortune 500 customers are now integrating MongoDB directly into lakehouse architectures rather than treating transactional databases and data lakes as separate systems.
A Fortune 500 client migrating to a cloud lakehouse isn't treating MongoDB as a separate transactional database — it wants MongoDB embedded inside the lakehouse itself. This signals a broader architectural shift toward unified data management that combines streaming, analytics, and AI in one platform.
MongoDB and Capgemini are targeting mainframe and AS400/DB400 modernization as a major upcoming partnership use case, with MongoDB offering out-of-the-box solutions.
Mainframe and AS400 modernization is emerging as one of the biggest near-term partnership opportunities for MongoDB and Capgemini. Legacy systems storing data in EBCDIC format are being migrated into MongoDB using out-of-the-box tooling, unlocking decades of enterprise data for AI workloads.
Beyond oil and gas, digital manufacturing, industrial IoT, connected vehicles, and fleet management are the next major use cases for the MongoDB–Capgemini partnership. These bridging physical-digital architectures represent a 5-year growth runway for joint solutions.
Vinay Makkaji sees a positive collaboration opportunity over the next 5 years between MongoDB, Capgemini, and hyperscalers across data modernization and industrial IoT.
MongoDB is no longer just a database choice for Capgemini — it's a co-investment partner protecting margins and accelerating multi-year transformation programs. In some cases, this co-innovation approach has delivered 30 to 50% improvement in outcomes.
Capgemini has seen almost 30 to 50% improvement in outcomes in some cases when leveraging the MongoDB partnership to accelerate transformation programs.
