Analysis of Spatial Database Performance for Location Intelligence
This study aims to examine the performance evaluation of the non-relational spatial database (NoSQL) for location intelligence. NoSQL means Not Only SQL database. It is an unstructured database which is a collection of non-relational data storage systems. Some of the existing NoSQL databases are Cassandra, CouchDB, Hadoop Hbase, MongoDB, etc. Location intelligence as a word is used more often to describe the new generation of GIS. These location-based data require lots of data uploaded into the database in other to keep current and relevant information from source devices (smartphones, laptops, etc.). NoSQL differs from the SQL where SQL stands for Structured Query Language, invented as a standard high-level interface for the management of relational database management systems (RDBMS). Databases based on the relational model include MySQL, MS-SQL Server, Oracle database, etc. The significance of this study is to evaluate NoSQL spatial database performance for location intelligence. The result of the evaluation can help businesses or organizations to know which database will have a better performance in term of location data. Thus, we conduct the experiments to outline the general differences between the SQL and NoSQL and also compare the speed performance of SQL and NoSQL databases for Location Intelligence based on throughput and minimize contention. The latency measured in the experiments shows how long each write or read request takes to be processed. From the result, MongoDB presents better best response time and high-performance throughput (i.e. scalability performance) than Oracle. However, the essential features such as the basic operation of geo-function support that Oracle provides were missing in MongoDB. Relational databases are still far superior if the user needs to calculate geoinformation on the database level. The results provided by this study are significant only for the chosen database settings but indicate that NoSQL databases are a possible alternative, at least for querying information about the attributes. In conclusion, it shows that both SQL and NoSQL databases have advantages and disadvantages when performed spatial queries over location intelligence.,
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