Views, objects, and persistence for accessing a high volume global data set

Efficient access methods are reviewed and explored in relation to the global surface hourly data set and several of its derivative products. Typical access paradigms are compared for object persistence using streamed output files, key/value databases, and object and relational databases (ODBMS/RDBMS). An overview of Java Data Objects (JDO), Enterprise Java Beans (EJB), and other alternatives to persist objects are given. Efficiencies gained by implementing RDBMS views or aggregates are also investigated. Given spatial, temporal, and analytical factors, a conservative estimate for the number of data objects from global hourly data approaches 2 billion.