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The application of blockchain technology in the online trading architecture of aquatic products can provide basic protection for the privacy information of both parties involved in the transaction. However, currently, blockchain-based aquatic product online trading models and systems are suffering from problems such as large data storage loads, high maintenance costs, and low data query efficiency. To further alleviate the above problems, based on the sorting and analysis of the aquatic product trading process, and according to the technical requirements of aquatic product trading business, a trading matching model for aquatic products based on multi-chain storage optimization was proposed. This model achieved a highly efficient multi-attribute online trading matching process for aquatic products through greedy algorithms in smart contracts, and constructed a multi-chain architecture for aquatic product online trading through blockchain multi-channel technology, achieving distributed storage of user transaction information and thus improving the efficiency of transaction information query. Meanwhile, this trading matching model adopted a dual storage technology of blockchain and local database, which alleviated the load of massive data storage at various nodes in the blockchain network. Then, a prototype system for aquatic product online trading based on multi-chain storage optimization was implemented on the Hyperledger Fabric platform. The performance test results of the prototype system indicated that it took 900s to complete 1296 transaction matchings on average, indicating that the system can operate normally when processing a volume of thousands of transaction data, meeting the needs of the online trading platform for aquatic products. At the same time, when storing 1600 contract information on the chain, the average time to query a user’s contract information was 4.018s, which indicated that the multi-chain data storage structure improved the speed of on-chain data queries.