The article explains how a schemaless JSON document model stored in a relational database can replace traditional relational tables for trading system orders, reducing schema change costs, improving flexibility, and ensuring consistency through version‑based optimistic locking and real‑time Elasticsearch indexing.
Uber built Schemaless, a MySQL‑backed, sharded JSON datastore with immutable cells, triggers, and secondary indexes, to overcome PostgreSQL limits and achieve linear scalability, high write throughput, reliable change notifications, and operational resilience for its ride‑hailing platform.
Uber’s Schemaless datastore, described in the Mezzanine project, replaces a single PostgreSQL node with a highly available, horizontally scalable MySQL‑backed key‑value store, detailing its architecture, data model, triggers, indexing, fault‑tolerance, and operational considerations for massive trip data.
This article explains how Uber engineered Schemaless, a highly available, horizontally scalable datastore built on MySQL that stores immutable JSON cells without a fixed schema, detailing its design goals, architecture, data model, trigger system, indexing strategy, and fault‑tolerant read/write mechanisms.
