The Healthcare domain has very critical data that affects lives. Therefore, this sector needs to utilize this data properly to improve its services, and patients care. Data mining techniques offer excellent analysis methods that can benefit healthcare service providers and patients. There are many available algorithms with various performances, each with pros and cons. However, every algorithm's usage depends on the application, data type, and other features involved. Moreover, vital healthcare prediction applications like heart disease detection, obesity prediction, and cesarean delivery operations forecasting need to be implemented with the support of the different DM approaches. Furthermore, using data mining tools for simple and better analysis results is of great support. Even with the great benefits it introduced, there are still many challenges facing data mining accomplishments. This paper provides an extensive overview of data mining in the healthcare sector. The researchers' contribution are: (1) the comprehensive overview of related elements that work as a basic introduction, (2) structure summary for the advantages and disadvantages of the common techniques, (3) the thoroughly description of the most used tools in healthcare, (4) the detailed comparison of the reviewed literature, and (5) the discussion and recommendations of future directions to benefit from data mining analytics in this field optimally.