In this paper, we describe and compare the emergent data mesh and data space paradigms. These socio-technical approaches aim to facilitate data sharing, but both of them has unique governance structures. We rely on design science research methodologies, including a structured literature review subsequently complemented by expert interviews, to highlight their idiosyncrasies, synergies, and differences. While data mesh primarily focuses on domain-oriented decentralization within a single organization, data space, by contrast, addresses inter-organizational data exchange, emphasizing data sovereignty. In this comparative analysis, we show how each approach offers distinct strategies for addressing data-sharing challenges, supporting their potential to converge and complement each other. These insights inform practitioners and researchers about best-fit scenarios, guiding adoption decisions. Ultimately, we propose a foundation for future studies to investigate the governance models further, elaborate on emerging convergences, explore technical connection points and refine guidelines for choosing the most effective paradigm.