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BaikalDB, Baidu's distributed storage system, evolves from an OLTP‑focused engine to a hybrid HTAP architecture by introducing a vectorized query engine and a massively parallel processing (MPP) layer, addressing compute and resource bottlenecks for large‑scale analytical workloads while preserving transactional guarantees.
This article examines the business storage requirements of large‑scale advertising platforms and details how BaikalDB was architected as a cloud‑native, MySQL‑compatible distributed database that combines OLTP, OLAP, KV and full‑text capabilities while ensuring high reliability, low cost and linear scalability.
Tongcheng Yilong’s BaikalDB deployment combines high‑availability multi‑Raft HA, HTAP support, and share‑nothing scalability to deliver over 72K TPS OLTP and ten‑fold faster OLAP queries while cutting operational costs up to a hundredfold through dual‑center, columnar storage and cloud‑native elasticity.
This article examines the requirements of commercial advertising systems for data storage, traces the evolution from single‑node MySQL to BaikalDB’s cloud‑native, MySQL‑compatible distributed architecture, and details its storage, compute, and scheduling designs, highlighting key features such as Raft replication, RocksDB storage, and hybrid OLTP/OLAP support.