Data Space Architecture and Metadata Models
The article outlines a data‑space architecture that employs a wide‑table design with dynamic columns and dedicated metadata tables, a metadata execution engine for business‑logic mapping, upgraded SQL parsing via Druid, MySQL‑proxy protocol handling, and distributed flow control using Redis and Zookeeper to enable scalable, multi‑tenant, low‑code and cloud‑native data management.