Geradores
Gerador de Dados Mock (Pro)
25+ field types — names, addresses, products, finance, lorem.
Schema · 8 field(s)
[
{
"id": "41936071-dfd7-ad91-2fee-8284fd2d7008",
"name": "Joan Clarke",
"email": "tony.knuth58@example.com",
"city": "Singapore",
"company": "Cyberdyne",
"joined_at": "2025-09-04",
"amount": "$990.29",
"active": true
},
{
"id": "1372c9c6-3404-5ef3-d955-2f1ec6b41813",
"name": "Hedy Hoare",
"email": "edsger.torvalds22@example.com",
"city": "Singapore",
"company": "Pied Piper",
"joined_at": "2025-07-30",
"amount": "$697.47",
"active": false
},
{
"id": "6228af6b-601d-fc26-47de-358460a5749b",
"name": "Ken Lamarr",
"email": "linus.knuth41@example.com",
"city": "Seoul",
"company": "Wayne Enterprises",
"joined_at": "2025-06-22",
"amount": "$949.99",
"active": false
},
{
"id": "e0488ffb-d49a-057c-f094-aa74b80dbeb8",
"name": "Brian Kernighan",
"email": "hedy.wirth5@example.com",
"city": "Mumbai",
"company": "Tyrell",
"joined_at": "2026-02-22",
"amount": "$747.48",
"active": true
},
{
"id": "f7599069-1214-486f-a95b-4ee8ab942315",
"name": "Frances Wirth",
"email": "hedy.clarke29@example.com",
"city": "Singapore",
"company": "Wonka",
"joined_at": "2026-01-15",
"amount": "$730.83",
"active": false
},
{
"id": "ca4cfce2-98b0-60d3-6fa9-179e22dfc13c",
"name": "Brendan Eich",
"email": "joan.hopper67@example.com",
"city": "Seoul",
"company": "Tyrell",
"joined_at": "2025-10-26",
"amount": "$890.89",
"active": false
},
{
"id": "c7c37932-62ca-331d-f661-1d4795b43fc0",
"name": "Joan Turing",
"email": "margaret.hamilton92@example.com",
"city": "Helsinki",
"company": "Soylent",
"joined_at": "2026-05-06",
"amount": "$784.58",
"active": true
},
{
"id": "e0b1b44d-b0d2-3b26-fc78-b308af36e94e",
"name": "Brian Lamarr",
"email": "hedy.kernighan34@example.com",
"city": "Tokyo",
"company": "Hooli",
"joined_at": "2025-11-05",
"amount": "$90.80",
"active": true
},
{
"id": "bdac7c22-6843-00c5-77d6-8d4928374f6c",
"name": "Brian Thompson",
"email": "joan.hamilton39@example.com",
"city": "Lisbon",
"company": "Tyrell",
"joined_at": "2026-03-03",
"amount": "$547.09",
"active": true
},
{
"id": "f52bcf8a-2c65-eda4-9220-b3c7ab108bd5",
"name": "Donald Kernighan",
"email": "margaret.wirth21@example.com",
"city": "Lisbon",
"company": "Stark Industries",
"joined_at": "2026-01-28",
"amount": "$288.01",
"active": false
},
{
"id": "c4a510e8-7e6d-2673-e4f5-911c2eba6305",
"name": "Niklaus Allen",
"email": "alan.hopper55@example.com",
"city": "Mumbai",
"company": "Stark Industries",
"joined_at": "2026-05-02",
"amount": "$866.81",
"active": true
},
{
"id": "fbec4928-ab73-99ee-417d-e995cccc57b6",
"name": "Donald Turing",
"email": "joan.dijkstra34@example.com",
"city": "Sydney",
"company": "Stark Industries",
"joined_at": "2025-11-04",
"amount": "$960.94",
"active": true
},
{
"id": "8496823a-f2be-9696-c839-e0a1b2be3d3e",
"name": "Linus Hopper",
"email": "tony.allen45@example.com",
"city": "Tokyo",
"company": "Globex",
"joined_at": "2026-04-08",
"amount": "$331.08",
"active": false
},
{
"id": "ef5d89ef-6817-4d1c-b1ad-7d7883ed5dcb",
"name": "Edsger Dijkstra",
"email": "donald.wirth26@example.com",
"city": "Tokyo",
"company": "Globex",
"joined_at": "2026-03-28",
"amount": "$265.91",
"active": false
},
{
"id": "88d15279-8b78-76b5-b759-6eea802b4435",
"name": "Ada Allen",
"email": "margaret.turing88@example.com",
"city": "Mumbai",
"company": "Stark Industries",
"joined_at": "2025-09-09",
"amount": "$927.74",
"active": false
},
{
"id": "c7dbfa58-5868-25b5-7f4a-9538ebfb4924",
"name": "Niklaus Kernighan",
"email": "hedy.dijkstra91@example.com",
"city": "Tokyo",
"company": "Hooli",
"joined_at": "2026-05-10",
"amount": "$837.78",
"active": true
},
{
"id": "97b61316-f8f8-2c0d-b2ee-98745f43e2b0",
"name": "Joan Hamilton",
"email": "hedy.lovelace72@example.com",
"city": "London",
"company": "Hooli",
"joined_at": "2025-11-01",
"amount": "$767.56",
"active": true
},
{
"id": "b1b3721e-23cd-bca4-c3f6-13df560fff6c",
"name": "Donald Hamilton",
"email": "margaret.knuth11@example.com",
"city": "Singapore",
"company": "Initech",
"joined_at": "2025-11-22",
"amount": "$598.82",
"active": false
},
{
"id": "5929db2c-0b5f-41f3-72f1-03590f4d9141",
"name": "Grace Kernighan",
"email": "alan.eich49@example.com",
"city": "Toronto",
"company": "Initech",
"joined_at": "2025-07-09",
"amount": "$793.65",
"active": true
},
{
"id": "1b9f10b4-b426-3c93-8b17-c2feed886779",
"name": "Alan Allen",
"email": "linus.hamilton73@example.com",
"city": "Seoul",
"company": "Tyrell",
"joined_at": "2026-03-19",
"amount": "$122.16",
"active": false
}
]Nota do editor
Understanding · Realistic-looking data, generated to fit a schema.
Este capítulo aprofundado está disponível apenas em inglês no momento. A ferramenta de conversão acima funciona no seu idioma; o artigo explicativo longo ainda não foi traduzido.
Perguntas frequentes
Quick answers.
›What data formats can I export?
The generator supports JSON, CSV, and SQL insert statements. You can also copy individual rows or the entire dataset directly to your clipboard.
›How many records can I generate at once?
You can generate up to 5,000 records per batch. Large batches are processed in your browser memory, so performance depends on your device hardware.
›Is the generated data truly random?
Yes. It uses a library of realistic values combined with randomisation to ensure variety in names, addresses, and secondary fields like `UUID` or `Lorem Ipsum` text.
›Can I define custom fields?
Select from over 25 predefined field types including personal details, commerce data, and technical identifiers. You can rename headers to match your specific database columns.
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