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Medallion vs Data Vault vs Data Mesh vs Dimensional Modeling

A common mistake in data architecture is asking 'which architecture is better?' The better question is: which problem are we trying to solve?

8 min read

A common mistake in data architecture is asking “which architecture is better?” The better question is “which problem are we trying to solve?” Different architectural patterns solve different problems.

Medallion Architecture — Purpose: Data Refinement

Bronze
Silver
Gold
  • Progressive data quality
  • Raw-data preservation
  • Data transformation
  • Batch + streaming
  • Analytics & AI pipelines

Data Vault — Purpose: Historical Enterprise Data Integration

Built around Hubs, Links, and Satellites. Useful when you have many source systems, complex enterprise integration, strong historical requirements, auditability, and frequently changing source systems.

Data Vault and Medallion don't necessarily compete — for example: Bronze for raw ingestion, Silver modeled as Data Vault, Gold for business models.

Dimensional Modeling — Purpose: Analytics & BI

Typical structures are fact tables and dimension tables — for example FactSales, DimCustomer, DimProduct, DimDate.

  • BI dashboards
  • Reporting
  • KPIs
  • Analytical workloads
  • Business-facing data marts

Medallion can provide the refinement pipeline while dimensional modeling structures the Gold layer.

Data Mesh — Purpose: Domain Ownership

Instead of one centralized team owning everything, domains like Finance, Healthcare, Supply Chain, Retail, and Marketing can own their respective data products.

  • Domain ownership
  • Data as a product
  • Self-service platform
  • Federated governance

Medallion can still be used inside individual domains.

Lakehouse — Purpose: Modern Data Platform

A Lakehouse brings together capabilities traditionally associated with a Data Lake, a Data Warehouse, and ML/AI.

Object Storage
Bronze
Silver
Gold
BI / ML / RAG / AI Agents / Applications

Medallion therefore can be a logical organization pattern inside a Lakehouse.

Modern Enterprise Architecture

These patterns can work together, end to end:

Sources (ERP, CRM, APIs, Kafka, SaaS)
Ingestion (Batch / CDC / Streaming)
Bronze — Raw + Auditable
Silver — Clean + Conformed + Integrated
Data Modeling (Data Vault / Dimensional / Domain Models)
Gold — Business Data Products
Consumption (BI / ML / RAG / Agentic AI / Applications)

Governance runs across all layers

  • Security
  • Quality
  • Lineage
  • Catalog
  • Observability

The key takeaway

  • Medallion — how data gets refined
  • Data Vault — how enterprise history is integrated
  • Dimensional Modeling — how analytics data is structured
  • Data Mesh — who owns and manages data
  • Lakehouse — where modern data workloads can operate
The best enterprise architecture often combines these patterns based on business requirements. Don't choose an architecture because it is popular.
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