a neural network resource sizing apparatus for database applications . through use of multiple database application metrics input into a neural network learning algorithm , recommended resource capacities are generated . input parameters such as the number of records , lookups , images , pdfs , fields , blobs and width of fields for example may be utilized to train a neural network to yield needed resource metrics such as the processing power , memory , disk and / or network capacities required to run the database application . training for the neural network may involve running tests over all desired cross interactions of input and output parameters beginning for example with a small repository and ending with the maximum complexity of data and schema test . the training data is input into the neural network for the given database application version and utilized to plan resource utilization . a portal or webservice may be utilized to provide an interface to the apparatus .