With the continuous expansion and refinement of seismic monitoring networks,seismic observation data have entered an era of explosive growth. As a result,the storage and efficient retrieval of massive datasets have become critical challenges. This paper proposes a seismic waveform data retrieval service based on a distributed technology architecture. the system employs the high-performance indexing capability of the Elasticsearch distributed search and analytics engine and integrates Ceph S3 distributed object storage as the underlying data infrastructure,thereby enabling millisecond-level full-text retrieval of FDSN-standard metadata. the service was deployed and tested on the infrastructure platform of the International Earthquake Science Data Center. Application results show that the service maintains high retrieval efficiency and system stability under high-concurrency conditions,significantly improving the efficiency of seismic waveform data acquisition for researchers. This study provides important technical support for the standardized management of massive seismic data and offers a valuable practical reference for the construction of next-generation seismic science data service systems.