Data Mesh is not a product, nor a specific tool. It’s an organizational model based on four core principles.
Scalable Data ArchitecturesA collection of 6 posts
Discover real-world cases of modern data stack adoption and design resilient architectures that optimize performance, cost, and flexibility across on-prem, multi-cloud, and hybrid environments.
Data Fabric is a logical architecture that unifies access to distributed data systems through virtualization, metadata-driven orchestration, and centralized governance.
A Data Lakehouse builds on the foundation of a Data Lake by adding core warehouse capabilities : transactional updates, etc.
A Hybrid Data Warehouse unifies two complementary ecosystems. It combines the structure and governance of a Data Warehouse for BI, with the scalability of a Data Lake for big data, ML, and diverse formats.
Traditional data warehousing follows a structured, schema-on-write approach. Data is ingested through ETL pipelines into a centralized data warehouse, often complemented by downstream data marts.
Today, we’ll take a step back and look at the big picture: how all data components come together to form a unified data architecture.