Yahoo Cloud Serving Benchmark

NEWS
Apr 28, 2010

With the many new serving databases available including Sherpa, BigTable, Azure and many more, it can be difficult to decide which system is right for your application, partially because the features differ between systems, and partially because there is not an easy way to compare the performance of one system versus another. The goal of the Yahoo Cloud Serving Benchmark (YCSB) project is to develop a framework and common set of workloads for evaluating the performance of different "key-value" and "cloud" serving stores. The project comprises two areas:
  • The YCSB Client, an extensible workload generator
  • The Core workloads, a set of workload scenarios to be executed by the generator
Although the core workloads provide a well-rounded picture of a system's performance, the Client is extensible so that you can define new and different workloads to examine system aspects, or application scenarios, not adequately covered by the core workload. Similarly, the Client is extensible to support benchmarking different databases. Although we include sample code for benchmarking HBase and Cassandra, it is straightforward to write a new interface layer to benchmark your favorite database. A common use of the tool is to benchmark multiple systems and compare them. For example, you can install multiple systems on the same hardware configuration, and run the same workloads against each system. Then you can plot the performance of each system (for example, as latency versus throughput curves) to see when one system does better than another.

Additional Resources



Download:

  • Ycsb v4.pdf
  • ACM COPYRIGHT NOTICE. Copyright © 2012 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept., ACM, Inc., fax +1 (212) 869-0481, or permissions@acm.org.