Ecommerce test data

FakeStoreDB

Realistic ecommerce test data. 6 relational tables, proper foreign keys, distributions that make sense. Validated across 164 million integrity checks.

6 tables 5 verticals 4 formats 164M checks, 0 issues

Built like a real database

6 normalized tables with real relationships — the kind of schema you'd build for a production ecommerce app. Every foreign key resolves. Every order total matches its line items.

customers 10 cols
  • customer_idPKINT
  • first_nameVARCHAR
  • last_nameVARCHAR
  • emailVARCHAR
  • phoneVARCHAR
  • addressVARCHAR
  • cityVARCHAR
  • stateVARCHAR
  • zip_codeVARCHAR
  • created_atDATETIME
orders 6 cols
  • order_idPKINT
  • customer_idFKINT
  • order_dateDATETIME
  • statusVARCHAR
  • total_amountDECIMAL
  • shipping_addressVARCHAR
order_items 6 cols
  • order_item_idPKINT
  • order_idFKINT
  • product_idFKINT
  • quantityINT
  • unit_priceDECIMAL
  • total_priceDECIMAL
categories 3 cols
  • category_idPKINT
  • nameVARCHAR
  • descriptionTEXT
products 8 cols
  • product_idPKINT
  • category_idFKINT
  • nameVARCHAR
  • descriptionTEXT
  • priceDECIMAL
  • skuVARCHAR
  • stock_quantityINT
  • created_atDATETIME
reviews 7 cols
  • review_idPKINT
  • product_idFKINT
  • customer_idFKINT
  • ratingINT
  • titleVARCHAR
  • commentTEXT
  • review_dateDATETIME

See the data

Real-looking rows, not Lorem ipsum. Names that sound like people, prices that follow market patterns, orders with proper line items.

> SELECT * FROM customers ORDER BY customer_id LIMIT 4;
customer_idfirst_namelast_nameemailcitystatecreated_at
1SarahChensarah.chen@email.comPortlandOR2024-01-03
2MarcusWilliamsm.williams@mail.comAustinTX2024-01-05
3PriyaPatelpriya.p@inbox.comSeattleWA2024-01-07
4JamesO'Brienj.obrien@webmail.comDenverCO2024-01-09
category_idnamedescription
1ElectronicsSmartphones, laptops, audio equipment, and accessories
2Home & KitchenFurniture, appliances, and kitchen essentials
3ClothingMen's and women's apparel, shoes, and accessories
4Sports & OutdoorsEquipment, activewear, and outdoor gear
product_idcategory_idnamepriceskustock_quantity
11Wireless Noise-Canceling Headphones89.99ELEC-WH-001342
21USB-C Fast Charging Cable 6ft12.99ELEC-CB-0471847
32Ceramic Pour-Over Coffee Dripper34.50HOME-CF-012156
43Merino Wool Crew Socks 3-Pack24.99CLTH-SK-0892103
order_idcustomer_idorder_datestatustotal_amountshipping_address
1422024-01-15delivered127.48814 NW Elm St, Portland OR
21872024-01-15shipped34.502209 S Congress Ave, Austin TX
332024-01-16processing214.97445 Pine St, Seattle WA
48912024-01-16delivered49.981032 Colfax Ave, Denver CO
order_item_idorder_idproduct_idquantityunit_pricetotal_price
111189.9989.99
212212.9925.98
323134.5034.50
431289.99179.98
review_idproduct_idcustomer_idratingtitlereview_date
11425Best headphones I've owned2024-02-01
211034Great sound, slightly tight fit2024-02-03
331875Perfect morning pour-over2024-01-28
44564Warm and durable2024-02-10

Built for real development

Not a toy dataset. Not Northwind from 1996. Designed for how you actually build and test modern apps.

01

Modern schema

Designed for 2024 ecommerce. Products have SKUs, orders have proper line items, reviews have ratings. The schema you'd actually build.

02

Realistic scale

From 100 customers for prototyping to 100K customers with 500K orders for load testing. Every tier maintains full referential integrity.

03

5 verticals

General, Electronics, Fashion, Home & Garden, Marketplace. Same schema, different product catalogs with category-appropriate names and pricing.

04

Your format

SQL (Postgres-compatible), CSV, JSON, SQLite. Every format, every tier, every vertical. Import into whatever you're building.

Pick your scale

Start free. Scale when you need more data, more verticals, or more formats.

Starter
Free
No account needed
  • 100 customers
  • 500 orders
  • General vertical
  • JSON + SQLite
  • Great for prototyping
Download Free
Scale
$79
  • 100,000 customers
  • 500,000 orders
  • 1.5M+ line items
  • 5 verticals
  • All 4 formats
  • Load testing & data pipelines
Get Scale

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