How are different components of subjective well-being (SWB) concurrently and prospectively related to each other? Several studies already addressed this research question. However, they suffer from a combination of important limitations such as exclusive attention on cognitive or affective indicators of SWB, over-reliance on cross-sectional data, or no explicit consideration of age effects or associations across domains. To overcome these limitations, we utilize the analytical exploratory power of psychometric network analysis combined with longitudinal data (years 2015-2019) from the most recent version (V37) of the German Socio-Economic Panel (SOEP). We analyze the associations between general life satisfaction, domain satisfaction (e.g., health, work, personal income, leisure time, family life, and dwelling), as well as positive and negative affect with a multi-level graphical vector auto-regression (GVAR) model. The estimations are performed with functions from the psychonetrics R Package. Longitudinal psychometric network analysis allows us to examine the complex multivariate relationships across the different components of subjective well-being while simultaneously differentiating between temporal, contemporaneous and between-subject associations. These associations are additionally compared across different age groups. Thus, our study provides new insights into the relationship of subjective well-being and satisfaction with different domains as well as their association with age.