Data Gravity: Architecting Around Where Data Lives

Data rarely stays neutral—it pulls systems toward it. Data Gravity is a cloud computing book devoted to understanding how the location, volume, and movement of data shape architecture, cost, and performance.
The writing explores why modern systems fail when data placement is ignored. As datasets grow, moving compute becomes cheaper than moving data, and architectures must adapt accordingly. Data gravity here is not a limitation—it is a design signal that guides smarter decisions.
Rather than focusing only on storage choices, the book examines system-wide impact. Readers learn how data locality affects latency, security, compliance, scalability, and cloud strategy. Each chapter shows how architectures succeed when services are designed around where data lives, not where it is convenient to process.
The tone is analytical and practical, aimed at architects and platform engineers. Language remains clear and structured, translating abstract concepts into concrete architectural trade-offs.
Data Gravity moves through data placement, distributed systems, hybrid and multi-cloud design, data movement costs, and governance—demonstrating how respecting data gravity leads to resilient, efficient systems.
Key themes explored include:
• Data locality and architecture
• Cost of data movement
• Compute near data
• Hybrid and distributed systems
• Designing with constraints
Data Gravity is for teams scaling data-heavy systems—offering guidance to architect intelligently around the true center of gravity.