A Narrative Review of Data Mesh Architecture Principles and Implementation Outcomes

Abstract

Centralised data architectures often create operational bottlenecks that limit organisational agility. Data Mesh offers a distributed alternative through domain ownership and federated governance. This narrative review synthesises 52 sources published between 2001 and 2024, examining the evolution from traditional data architectures to Data Mesh implementations across financial services, healthcare, e-commerce, and technology sectors. The review traces the progression from centralised data warehouses through distributed computing frameworks to Data Mesh's emergence, identifying four foundational principles domain-oriented decentralisation, data as a product, self-serve infrastructure, and federated governance. Analysis of recent implementation studies reveals mixed outcomes. Successful adoptions demonstrate improved domain autonomy and reduced central bottlenecks. However, multiple case reports significant coordination complexity and extended implementation timelines, with transformations requiring substantial investments in platform engineering. Consistent challenges emerge, including skill gaps in domain teams transitioning to data ownership, policy conflicts in federated governance structures, infrastructure investments that exceed traditional architectures, and cultural resistance to distributed accountability. Implementation success correlates with existing DevOps maturity, sustained executive sponsorship, phased adoption approaches, and robust metadata management capabilities. The review identifies critical research gaps in standardised success metrics, quantitative failure analysis, privacy-preserving techniques for federated environments, and long-term sustainability assessment. Based on the analysed cases, Data Mesh appears most suitable for large enterprises with diverse data domains and established platform engineering capabilities. Smaller organisations may find centralised approaches more appropriate given the complexity and resource requirements of distributed architectures. This synthesis provides practitioners with evidence-based insights while highlighting priorities for future research.