GraphQL as a Data Mesh Access Layer in Global Banking
summary
Mega-bank replaces brittle cross-domain feeds with a metadata-driven supergraph architecture built on GraphQL + OpenTelemetry and integrated query engines, onboarding ~1,000 systems and ~100 stakeholders into a federated data mesh. The supergraph exposes a unified semantic model for composition, selection and aggregation, convinces domains to publish metadata (not full APIs), and hits production in ~18 months; early results show faster time-to-market, simpler integrations, better audit evidence and an estimated 2/3 reduction in producer/consumer data effort.
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chapters (12)
- 0:00Introduction and background
- 2:29Data governance challenges in banking
- 8:48Rethinking data delivery models
- 13:02Choosing data mesh over data fabric
- 18:02Key objectives for the project
- 19:05Evaluating GraphQL for data composition
- 21:13Implementing the supergraph architecture
- 23:47Designing data domains with unified semantics
- 25:36Persona-driven metadata experiences
- 29:49Brownfield vs. greenfield adoption
- 31:15Deprecating data in GraphQL
- 32:43Consumer types and use cases
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