Cloud-native databases have emerged as a hot topic in the field of database development in the era of cloud computing, thanks to their advantages such as out-of-the-box functionality, elastic scalability, and pay-as-you-go pricing. However, mainstream cloud-native databases only support a single master node to execute write transactions. This limitation hampers the system's ability to handle write-intensive workloads, making it difficult to meet the demands of businesses with high write requirements. To address this issue, this paper proposes the D3C (deterministic concurrency control cloud database) architecture, which achieves cloud-native multi-writer capabilities by designing a transaction processing mechanism based on deterministic concurrency control. D3C splits transactions into sub-transactions and independently executes them on various nodes according to a pre-defined global order, ensuring serializable isolation for transaction execution on multiple read-write nodes. Additionally, this paper introduces mechanisms such as asynchronous batch data persistence mechanisms based on multi-version to ensure the performance of multi-writer transaction processing, and proposes a consistency point-based fault recovery mechanism to achieve high availability. Experiments have shown that D3C can achieve 5.1 times the throughput of a traditional single-master architecture in write-intensive scenarios, while meeting the key requirements of cloud-native databases.