Streaming REST APIs for Large Financial Transaction Exports from Relational Databases

Researcher Abhiram Kandiraju has published a paper detailing a novel streaming architecture for REST APIs that handle massive financial transaction exports. Traditional APIs for this purpose typically construct complete export payloads—sometimes containing millions of records—in application memory before sending a single byte to the client. This approach causes high memory consumption and delays the initial response, creating bottlenecks for reporting, auditing, and compliance workflows. Kandiraju's design fundamentally changes this by integrating database cursor retrieval with progressive HTTP transmission.

Implemented using a Java-based JAX-RS framework with the StreamingOutput interface, the architecture fetches records incrementally from relational databases and writes them directly to the HTTP response stream. This means data delivery begins immediately and continues as records are processed, rather than waiting for a full dataset assembly. The system supports key financial formats like CSV, OFX, QFX, and QBO. In practice, this streaming method drastically cuts memory buffering needs and allows large export downloads to start without delay, enhancing both user experience and backend scalability for enterprise financial platforms dealing with high-volume data operations.