论文信息 - The Development of a Benchmark Tool for NoSQL Databases

The Development of a Benchmark Tool for NoSQL Databases

The aim of this article is to describe a proposed benchmark methodology and software application targeted at measuring the performance of both SQL and NoSQL databases. These represent the results obtained during PhD research (being actually a part of a larger application intended for NoSQL database management). A reason for aiming at this particular subject is the complete lack of benchmarking tools for NoSQL databases, except for YCBS [1] and a benchmark tool made specifically to compare Redis to RavenDB. While there are several well-known benchmarking systems for classical relational databases (starting with the canon TPC-C, TPC-E and TPC-H), on the other side of databases world such tools are mostly missing and seriously needed.

Ion Lungu | Bogdan George Tudorica

[1] Jim Gray,et al. Benchmark Handbook: For Database and Transaction Processing Systems , 1992 .

[2] Rim Moussa. TPC-H Benchmark Analytics Scenarios and Performances on Hadoop Data Clouds , 2012, NDT.

[3] David J. DeWitt,et al. Can the Elephants Handle the NoSQL Onslaught? , 2012, Proc. VLDB Endow..

[4] Rick Cattell,et al. Scalable SQL and NoSQL data stores , 2011, SGMD.

[5] Jing Zhao,et al. Benchmarking cloud-based data management systems , 2010, CloudDB '10.

[6] Adam Silberstein,et al. Benchmarking cloud serving systems with YCSB , 2010, SoCC '10.

[7] Cristian Bucur,et al. A comparison between several NoSQL databases with comments and notes , 2011, 2011 RoEduNet International Conference 10th Edition: Networking in Education and Research.

[8] Jianliang Xu,et al. Proceedings of the second international workshop on Cloud data management , 2010, CIKM 2010.

[9] George Tudorica Bogdan. Challenges for the NoSQL systems: Directions for Further Research and Development , 2013 .

[10] Tudorica Bogdan George,et al. A Research On Retrieving And Parsing Of Multiple Web Pages For Storing Them In Large Databases , 2012 .

[11] Ying Liu,et al. Understanding Grid resource information management through a synthetic database benchmark/workload , 2004, IEEE International Symposium on Cluster Computing and the Grid, 2004. CCGrid 2004..