  Julia is a new language for writing data analysis programs that are easy to
implement and run at high performance. Similarly, the Dynamic Distributed
Dimensional Data Model (D4M) aims to clarify data analysis operations while
retaining strong performance. D4M accomplishes these goals through a
composable, unified data model on associative arrays. In this work, we present
an implementation of D4M in Julia and describe how it enables and facilitates
data analysis. Several experiments showcase scalable performance in our new
Julia version as compared to the original Matlab implementation.
