TY - GEN
T1 - Quantitative analysis of consistency in NoSQL key-value stores
AU - Liu, Si
AU - Nguyen, Son
AU - Ganhotra, Jatin
AU - Rahman, Muntasir Raihan
AU - Gupta, Indranil
AU - Meseguer, José
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - The promise of high scalability and availability has prompted many companies to replace traditional relational database management systems (RDBMS) with NoSQL key-value stores. This comes at the cost of relaxed consistency guarantees: key-value stores only guarantee eventual consistency in principle. In practice, however, many key-value stores seem to offer stronger consistency. Quantifying how well consistency properties are met is a non-trivial problem. We address this problem by formally modeling key-value stores as probabilistic systems and quantitatively analyzing their consistency properties by statistical model checking. We present for the first time a formal probabilistic model of Apache Cassandra, a popular NoSQL key-value store, and quantify how much Cassandra achieves various consistency guarantees under various conditions. To validate our model, we evaluate multiple consistency properties using two methods and compare them against each other. The two methods are: (1) an implementation-based evaluation of the source code; and (2) a statistical model checking analysis of our probabilistic model.
AB - The promise of high scalability and availability has prompted many companies to replace traditional relational database management systems (RDBMS) with NoSQL key-value stores. This comes at the cost of relaxed consistency guarantees: key-value stores only guarantee eventual consistency in principle. In practice, however, many key-value stores seem to offer stronger consistency. Quantifying how well consistency properties are met is a non-trivial problem. We address this problem by formally modeling key-value stores as probabilistic systems and quantitatively analyzing their consistency properties by statistical model checking. We present for the first time a formal probabilistic model of Apache Cassandra, a popular NoSQL key-value store, and quantify how much Cassandra achieves various consistency guarantees under various conditions. To validate our model, we evaluate multiple consistency properties using two methods and compare them against each other. The two methods are: (1) an implementation-based evaluation of the source code; and (2) a statistical model checking analysis of our probabilistic model.
UR - http://www.scopus.com/inward/record.url?scp=84944717924&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-22264-6_15
DO - 10.1007/978-3-319-22264-6_15
M3 - Conference contribution
AN - SCOPUS:84944717924
SN - 9783319222639
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 228
EP - 243
BT - Quantitative Evaluation of Systems - 12th International Conference, QEST 2015, Proceedings
A2 - Campos, Javier
A2 - Haverkort, Boudewijn R.
PB - Springer
T2 - 12th International Conference on Quantitative Evaluation of Systems, QEST 2015
Y2 - 1 September 2015 through 3 September 2015
ER -