This paper presents our preliminary results developing an incremental query and transformation engine for our modeling framework. Our prior framework combined $\texttt{WebGME}$, a cloud-based collaborative modeling tool, with $\texttt{FORMULA}$, a language and tool for specifying and analyzing domain-specific modeling languages. While this arrangement has been successful for defining non-trivial languages in domains like CPS, one ongoing challenge is the scalability of executing model queries and transformations on large models. The inherent $\textit{incremental}$ nature of the modeling process exacerbates this scalability issue: model queries and transformations are repeatedly performed on incrementally updated models. To address this issue, we are developing an incremental version of $\texttt{FORMULA}$ that can perform efficient model queries and transformations in the face of continual model updates. This paper describes our experiences designing this incremental version, including the challenges we faced and design decisions. We also report encouraging benchmark results.