Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Conceptual Modeling for Customized XML Schemas
ER '02 Proceedings of the 21st International Conference on Conceptual Modeling
Bigtable: a distributed storage system for structured data
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
G-Store: a scalable data store for transactional multi key access in the cloud
Proceedings of the 1st ACM symposium on Cloud computing
Low overhead concurrency control for partitioned main memory databases
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Schism: a workload-driven approach to database replication and partitioning
Proceedings of the VLDB Endowment
Principles of Distributed Database Systems
Principles of Distributed Database Systems
Data Management in the Cloud: Challenges and Opportunities
Data Management in the Cloud: Challenges and Opportunities
Programming Google App Engine
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The design of the NoSQL schema has a direct impact on the scalability of web applications. Especially for developers with little experience in NoSQL stores, the risks inherent in poor schema design can be incalculable. Worse yet, the issues will only manifest once the application has been deployed, and the growing user base causes highly concurrent writes. In this paper, we present a model checking approach to reveal scalability bottlenecks in NoSQL schemas. Our approach draws on formal methods from tree automata theory to perform a conservative static analysis on both the schema and the expected write-behavior of users. We demonstrate the impact of schema-inherent bottlenecks for a popular NoSQL store, and show how concurrent writes can ultimately lead to a considerable share of failed transactions.