Distributed SQL

📖 Bản tiếng Việt (Vietnamese Edition) Series Navigation: This is Part 2 of the Core Banking Systems Architecture Masterclass. For the complete architectural curriculum, start at the Master Overview Guide. Distributed SQL ACID Latency: TiDB, CockroachDB & Spanner Answer-first: Distributed SQL engines achieve horizontal write scalability and multi-datacenter fault tolerance by pairing Multi-Raft or Paxos replication with bounded distributed clock synchronization. However, cross-node consensus introduces unavoidable speed-of-light physical latency penalties. While local metro Raft commits complete in 2ms to 5ms, cross-region transactions (such as cross-region WAN links between financial centers) require 15ms to 45ms per commit round trip. Core banking platforms mitigate this through locality-aware range leasing, pipelined Percolator commit protocols, and asynchronous inter-region Saga choreography. ...

← Previous Chapter: Part 3: Caching Strategies & Redis/Valkey | Series Hub: System Design Masterclass | Next Chapter: Part 5: Asynchronous Messaging, Kafka KRaft & Event-Driven Systems → Prerequisite: Read Part 3: Caching Strategies, Redis/Valkey & Stampede Prevention to understand how memory caching shields databases before scaling storage horizontally. Answer-first: Scaling relational databases beyond vertical hardware limits requires horizontal sharding by consistent tenant keys, managing read-replica replication lag with GTID session tracking, and migrating toward Multi-Raft distributed SQL engines. Deploying Vitess VTGate or CockroachDB eliminates the single-node storage bottleneck while preserving ACID guarantees and sub-20ms P99 commit latencies across distributed clusters. ...