We are currently using ArangoDB as a migration database (100.000 JSON files, 50 GB data, about 25% of the JSON files contain base64 encoded images, PDF files etc.). I wrote a custom import script for the data that takes about 90 minutes for the import using pyArango - one JSON file at a time...working nicely so far. Question: would it make sense parallelize the import in order to speed up the import process? Or is the performance of ArangoDB CPU/IO bound for such mass imports? We are running a standard standalone installation of ArangoDB 3.4.5 on a local SDD...no fancy setup.
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