This article provides a concise overview of four key distributed file systems—HDFS, CephFS, GFS, and TFS—explaining their architectures, strengths, weaknesses, and typical application scenarios for large‑scale data storage and processing.
This article examines Google’s unconventional infrastructure, detailing how millions of inexpensive PC‑level servers, custom power supplies, and proprietary networking support massive scale, and explains the core platforms—Google File System, MapReduce, and BigTable—that enable fast, reliable search and data processing across the globe.
This article explains the fundamentals of distributed file systems by linking Google’s GFS, MapReduce, and BigTable concepts to Hadoop’s open‑source implementation, covering terminology, architecture, server roles, data distribution, RPC protocols, file operations, fault recovery, consistency, load balancing, and garbage collection.
This article surveys common distributed file systems such as GFS, HDFS, Lustre, Ceph, GridFS, MogileFS, TFS, and FastDFS, explaining their origins, key characteristics, typical use cases, and practical considerations for large‑scale storage.
