Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-22264-6_15 | LITES |
Field | DocType | Volume |
Data mining,Eventual consistency,Sequential consistency,Computer science,NoSQL,Relational database management system,Probabilistic logic,Consistency model,Strong consistency,Database,Scalability | Conference | 4 |
Issue | ISSN | ISBN |
1 | 0302-9743 | 978-3-319-22263-9 |
Citations | PageRank | References |
6 | 0.43 | 20 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Si Liu | 1 | 42 | 4.43 |
| Nguyen Son | 2 | 42 | 11.72 |
| Jatin Ganhotra | 3 | 7 | 0.87 |
| Muntasir Raihan Rahman | 4 | 455 | 21.21 |
| Indranil Gupta | 5 | 1837 | 143.92 |
| José Meseguer | 6 | 9533 | 805.39 |