E-commerce sample database — MongoDB, embedded (6,622 rows)

Tables that belong to another are folded into it as arrays, so the documents read the way the application uses them. The rest are collections of their own, joined by key as in the flat version.

Load it:
  sh import.sh                    (into mongodb://localhost:27017)
  sh import.sh "<connection string>"

Or one collection at a time: mongoimport --db ecommerce --collection <name> --file <name>.ndjson

Collections:
  addresses — 90 documents
  audit_logs — 20 documents
  brands — 40 documents
  cart_items — 100 documents
  categories — 22 documents
  countries — 1 documents
  discount_coupons — 80 documents
  order_items — 1,000 documents
  order_returns — 20 documents
  order_statuses — 6 documents
  orders — 360 documents
  payment_methods — 5 documents
  payments — 350 documents
  product_attribute_values — 1,200 documents
  product_attributes — 4 documents
  product_reviews — 60 documents
  products — 400 documents, each with its product_images, its product_inventories
  return_reasons — 6 documents
  shipments — 340 documents
  shipping_methods — 5 documents
  shopping_carts — 60 documents
  suppliers — 30 documents
  support_messages — 35 documents
  support_tickets — 10 documents
  tax_rates — 12 documents
  users — 70 documents
  warehouses — 6 documents
  wishlists — 30 documents, each with its wishlist_items

Folded in (no collection of their own):
  product_images — 1,000 rows, as the "product_images" array on products (its product_id is the parent's _id)
  product_inventories — 1,200 rows, as the "product_inventories" array on products (its product_id is the parent's _id)
  wishlist_items — 60 rows, as the "wishlist_items" array on wishlists (its wishlist_id is the parent's _id)

Types: numeric columns are Decimal128, so totals stay exact; dates and timestamps are
Date values read as UTC (the data has no time zone); times and UUIDs are strings;
JSON columns are embedded objects.

Synthetic data, CC0-1.0, from databasesample.com. The same rows as the SQL and CSV files.
