The potential Big Data offers to organizations is widely recognized; however, translating this potential into business value requires a certain level of maturity. Maturity models have emerged as valuable tools to help organizations assess their current state and guide their progress toward higher maturity levels. We conducted this systematic literature review to explore and evaluate existing Big Data Maturity Models (BDMMs) and draw insights from related domains that could be transferred to the Big Data context. The final selection included 72 papers, 18 presenting BDMMs. The findings reveal consistent patterns across models in terms of design approach, architecture, purpose, and typology, with some distinctions in orientation and domain applicability. Notably, most models are primarily descriptive and only a few have the capacity for prescriptive use. Key limitations include a lack of detailed documentation and the absence of support tools, such as assessment software and visualization reports to aid decision-making.