Hybrid transactional/analytical processing (HTAP) database systems have gained extensive acknowledgment of users due to their full processing support of the mixed workloads in one system, i.e., transactions and analytical queries. Most HTAP database systems tend to maintain multiple data versions or additional replicas to accomplish online analytical processing (OLAP) without downgrading the write performance of online transactional processing (OLTP). This leads to a consistency problem between the data of TP and AP versions. Meanwhile, HTAP database systems face the core challenge of achieving efficient data sharing under resource isolation, and the data-sharing model integrates the trade-off between business requirements for performance and data freshness. To systematically explain the data-sharing model and optimization strategies of existing HTAP database systems, this study first utilizes the consistency models to define the data-sharing model and classify the consistency models for HTAP data sharing into three categories, namely, linear consistency, sequential consistency, and session consistency, according to the differences between TP generated versions and AP query versions. After that, it takes a deep dive into the whole process of data-sharing models from three core issues, i.e., data-version number distribution, data version synchronization, and data version tracking, and provides the implementation methods of different consistency models. Furthermore, this study takes a dozen of classic and popular HTAP database systems as examples for an in-depth interpretation of the implementation methods. Finally, it summarizes and analyzes the optimization strategies of version synchronization, tracking, and recycling modules involved in the data-sharing process and predicts the optimization directions of the data-sharing models. It is concluded that the self-adaptability of the data synchronization scope, self-tuning of the data synchronization cycle, and freshness-bound constraint control under sequential consistency are the possible means for better performance of HTAP database systems and higher freshness.