Which DataRaptor type should you use to retrieve data from a single object while preserving the output structure?

Which DataRaptor type should you use to retrieve data from a single object while preserving the output structure?

• A. DataRaptor Turbo Extract
• B. DataRaptor Transform
• C. DataRaptor Load
• D. DataRaptor Extract

Answer: (A)

DataRaptor Turbo Extract is designed for fast retrieval of data from a Salesforce object while keeping the output in the exact structure you define. When you pull data from a single object and you want the resulting payload to mirror the object's hierarchical layout, Turbo Extract delivers both performance and a predictable, preserved output shape. This makes it ideal for straightforward, single-object extractions where the consumer expects a consistent, tree-like response. Other options serve different purposes. A standard Extract also fetches data but isn’t optimized for speed or guaranteed preservation of the full output tree in all scenarios. A DataRaptor Transform is used to reshape or map data after extraction, not for the initial retrieval. DataRaptor Load is for writing data into Salesforce or another system, not for extracting data.

DataRaptor Turbo Extract is designed for fast retrieval of data from a Salesforce object while keeping the output in the exact structure you define. When you pull data from a single object and you want the resulting payload to mirror the object's hierarchical layout, Turbo Extract delivers both performance and a predictable, preserved output shape. This makes it ideal for straightforward, single-object extractions where the consumer expects a consistent, tree-like response.

Other options serve different purposes. A standard Extract also fetches data but isn’t optimized for speed or guaranteed preservation of the full output tree in all scenarios. A DataRaptor Transform is used to reshape or map data after extraction, not for the initial retrieval. DataRaptor Load is for writing data into Salesforce or another system, not for extracting data.