Meituan Large‑Scale KV Storage: Challenges and Architectural Practices

The article details Meituan’s evolution of KV storage, analyzes scalability and availability challenges of both in‑memory (Squirrel) and persistent (Cellar) systems, and presents concrete architectural solutions such as gossip optimization, fork‑less RDB, multi‑threading, bulkload, and cross‑region disaster recovery, while outlining future directions like Zookeeper removal and vector engine support.

CellarKV storageScalability

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Meituan Large‑Scale KV Storage: Challenges and Architectural Practices

DeWu Technology

Nov 20, 2023 · Backend Development

State Machine Evaluation and Selection for Product Domain

The article analyzes DeWu’s product lifecycle, explains New, Product, and Draft types, introduces state‑machine fundamentals, compares Java enum, Spring, Squirrel, and Cola implementations, benchmarks their throughput (showing Cola vastly faster), and concludes that despite Cola’s performance, Spring StateMachine is chosen for its richer features and seamless Spring integration.

COLAJavaSquirrel

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State Machine Evaluation and Selection for Product Domain

Meituan Technology Team

Jul 2, 2020 · Databases

Meituan's Million‑Level KV Storage Architecture and Practices: Squirrel (In‑Memory) and Cellar (Persistent)

Meituan’s KV platform evolved from Memcached and Redis to its own high‑throughput in‑memory Squirrel and durable Cellar systems, each partitioning keys into 16 384 slots, using ZooKeeper routing, Kubernetes scaling, intelligent migration, cross‑region Raft replication, multi‑queue latency isolation, and hotspot management, while planning further optimizations such as Redis‑Gossip tuning, kernel‑bypass I/O, and FPGA acceleration.

CellarKV storageMeituan

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Meituan's Million‑Level KV Storage Architecture and Practices: Squirrel (In‑Memory) and Cellar (Persistent)