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In a typical data warehouse, materialized views are used to speed up query execution. Upon updates to the base relations in the warehouse, these materialized views must also be maintained. The need to maintain these materialized views can have a negative impact on performance that is exacerbated in parallel RDBMSs, since simple single-node updates to base relations can give rise to expensive all-node operations for materialized view maintenance. We present a comparison of three materialized join view maintenance methods in a parallel RDBMS, which we refer to as the naive, auxiliary relation, and global index methods. The last two methods improve performance at the cost of using more space. The results of this study show that the method of choice depends on the environment, in particular, the update activity on base relations and the amount of available storage space.