With the increasing application of blockchain technology in critical domains such as financial technology and supply chain management, hybrid storage architectures that combine the high performance of traditional databases with the high trustworthiness of blockchains have become a research hotspot. However, existing solutions generally fail to systematically address the architectural incompatibilities between databases and blockchains, which manifest in three core technical challenges: transaction model differences, performance-cost contradictions, and data lifecycle management difficulties. To address these challenges, this study proposes and implements TDSM, a CDC-based database-blockchain synchronization system for achieving efficient and trustworthy data synchronization in heterogeneous environments. First, the study designs a lightweight atomic commit protocol integrated with verifiable revocation proofs and utilizes sparse Merkle trees to generate cryptographic proofs for deletion operations, ensuring the atomic mapping of cross-system transactions without introducing heavyweight two-phase commit, and thus achieving trusted on-chain auditing of the complete data lifecycle. Second, it proposes a resource-aware adaptive batching algorithm, which dynamically adjusts batching strategies by monitoring on-chain transaction costs in real time, effectively resolving the contradiction between the high throughput of databases and the high cost of blockchains. Experimental results demonstrate that TDSM maintains high throughput while significantly reducing synchronization costs. The adaptive batching mechanism achieves substantial resource savings compared to fixed strategies, the revocation proof mechanism remains efficient when processing large numbers of deletion operations, and the atomicity guarantee mechanism ensures data consistency across various failure scenarios.