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This paper details Cassandra, a decentralized structured storage system designed for managing massive amounts of structured data across numerous commodity servers. High availability and scalability are key features, achieved through techniques like consistent hashing for data partitioning and replication strategies across multiple data centers to handle failures. The system uses a simple data model and API, emphasizing write throughput without sacrificing read efficiency. The paper explores the system architecture, including failure detection, membership, and bootstrapping, along with practical experiences and performance metrics from its use at Facebook. Future work focuses on adding compression and enhanced atomicity.

https://www.cs.cornell.edu/projects/ladis2009/papers/lakshman-ladis2009.pdf

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