Designing performance monitoring tool for NoSQL Cassandra distributed database
Prasanna Bagade, Ashish Chandra, Aditya B. Dhende
Abstract
Prasanna Bagade, Ashish Chandra, Aditya B. Dhende
Abstract
The popularity of NoSQL databases (especially Cassandra) has been increasing day by day. Now, as many companies are developing Cassandra applications, they may need new tools to monitor database performance efficiently. Developers have difficulty optimizing something they can't see. When problems related to performance occur and proper analysis is needed, the statistical data generated by monitoring tool will be of a lot help. To optimize NoSQL applications, developers need to have an idea about how the database is behaving in different working scenarios. Cassandra is easy to configure, but for the proper performance tuning it is necessary to study the performance requirements for a particular application. This can be judged by monitoring tool. The paper describes the design of such monitoring tool and the results generated ie. statistics and graphs. The tool will be used primarily for low end machines as they are cost effective.
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The popularity of NoSQL databases (especially Cassandra) has been increasing day by day. Now, as many companies are developing Cassandra applications, they may need new tools to monitor database performance efficiently. Developers have difficulty optimizing something they can't see. When problems related to performance occur and proper analysis is needed, the statistical data generated by monitoring tool will be of a lot help. To optimize NoSQL applications, developers need to have an idea about how the database is behaving in different working scenarios. Cassandra is easy to configure, but for the proper performance tuning it is necessary to study the performance requirements for a particular application. This can be judged by monitoring tool. The paper describes the design of such monitoring tool and the results generated ie. statistics and graphs. The tool will be used primarily for low end machines as they are cost effective.
Key concepts: NoSQL, Computer science, Database, Popularity, Distributed database, Psychology, Social psychology, Scalability