Bulk vs batch import: API design guidance

James Higginbotham's article delves into the intricacies of API design, specifically focusing on bulk and batch import methods, and how these approaches are critical in efficiently managing large data imports. The article differentiates between bulk imports, which involve a single request to handle a large dataset, and batch imports, which break down data into manageable parts, each processed separately. Bulk imports are efficient for moving large datasets, but may strain API performance, while batch imports, though potentially slower, help avoid overwhelming the system by limiting payload sizes. The text highlights the importance of understanding these processes for optimizing API interactions, including considerations for error handling and adaptive sync versus async processing designs. Additionally, the article suggests using tools like Tyk to facilitate bulk and batch import needs, emphasizing the significance of selecting appropriate content types and response codes to conserve resources and adapt to varying circumstances.