<p>The interaction between identity and data is the key fulcrum to promote the coordinated development and industrial transformation of the Industry 4.0. The existing research usually adopts the smokestack industrial production mode to solve the problem of identity and interaction but ignores the leakage in the process of massive data query and the query efficiency. As a core technology for privacy protection, blockchain provides a feasible solution for interaction between data sharing and identity, however, issues such as the scalability of blockchain, the efficiency of data retrieval on the chain, and the security of data off the chain have not been effectively addressed. To address these problems, we propose a method (BOEDR) for data retrieval in Industry 4.0 to improve the efficiency of data queries without revealing privacy information. In BOEDR, we put forward an effective data prefix hash and an improved red–black tree &amp; buffer index without changing the characteristics of the blockchain to improve the efficiency of the retrieval interaction between the identity and its data in the blockchain. Moreover, the proposed BOEDR adopts SM4 to encrypt the Industrial identification data, which can provide the security of transmission and storage. In addition, we provide a security analysis of the Kafka consensus mechanism applied in the proposed scheme. Finally, we conduct a thorough experiment on the performance and interaction efficiency of the BOEDR. Compared with the existing industrial Internet identity resolution methods, the BOEDR improved the overall efficiency by 5%, optimized the time of 5ms per 10,000 queries, and delivered a 1.3s per million data insertions boost. At the same time, compared with existing solutions, there are significant improvements in blockchain performance and retrieval time.</p>