Which approach to load the data is FASTEST?
Upload the data to Amazon S3 and use the Loader command to load the data from Amazon S3 into the Neptune database.
Write a utility to read the data from the on-premises storage and run INSERT statements in a loop to load the data into the Neptune database.
Use the AWS CLI to load the data directly from the on-premises storage into the Neptune database.
Use AWS DataSync to load the data directly from the on-premises storage into the Neptune database.
Explanations:
Uploading data to Amazon S3 and using the Loader command is the fastest and most efficient method for loading large datasets (such as 25 GB) into Amazon Neptune. The Neptune bulk loader can process data in parallel, offering optimized performance when loading data from S3.
Running INSERT statements in a loop would be very slow for large datasets. It would be inefficient and impractical for 25 GB of data, as it involves processing each row individually, which severely impacts performance.
Using the AWS CLI to load data directly from on-premises storage into Neptune would not be as fast as using S3 as an intermediary. The CLI doesn’t provide the parallel processing capabilities of the Neptune bulk loader.
AWS DataSync is designed for transferring data to Amazon S3 or between file systems, not directly into databases like Neptune. It is not suitable for loading data directly into Neptune.
I structure that the answer is:
Upload the data to Amazon S3 and use the Loader command to load the data from Amazon S3 into the Neptune database.
If I’m not mistaken, the answer is:
Upload the data to Amazon S3 and use the Loader command to load the data from Amazon S3 into the Neptune database.