New and emerging spatial omics technologies continue to advance the study of the role of tissue architecture and morphology in various biological processes, including cellular phenotypes and crosstalk. The different platforms that provide spatial imaging or sequencing based solutions cover a range of spatial resolutions and often provide multi-layered information. Different molecular analyses and tissue structures can be captured in uni- or multi-modal datasets. Integration of information is key for understanding intricate biological processes in both discovery and clinical research. However, representing and handling spatial data efficiently, including combining multiple modalities or different spatial scales in a scalable and intuitive manner, remains a substantial challenge. Here, we present Giotto Suite, open-source software aimed at creating a fully modular and integrated spatial data analysis toolbox. At its core, it is centered around an innovative and technology agnostic framework embedded in the R software environment. Our implementation can represent virtually any type of spatial dataset and simultaneously provide scalable and extensible solutions from raw data processing to visualization. Giotto Suite disentangles morphology, spatial, and feature information to create a responsive and flexible workflow to analyze spatial data at multiple resolutions. By building interoperability interfaces and creating data structures that bridge the established fields of genomics and spatial data science in R, Giotto Suite aims to create an immersive ecosystem for spatial data analysis and tool development. We demonstrate the flexibility and use of Giotto Suite on several state-of-the-art spatial technologies and illustrate the unique features of our framework and how it can be easily extended to create custom engineered solutions for spatial data analysis.