Paste a JSON array, get a Snowflake DDL with NUMBER and TIMESTAMP_NTZ types.
Open the Schema Inferrer →Snowflake handles JSON natively via the VARIANT type, but for high-volume analytics it's faster to land the data into a typed table. The schema inferrer reads your JSON sample and emits a Snowflake CREATE TABLE with NUMBER(p,s) for decimals, BOOLEAN for true/false, and TIMESTAMP_NTZ/TIMESTAMP_TZ chosen from the timestamp shape.
Sample values and the dialect-native type they map to.
| Sample value | Inferred type |
|---|---|
| "qty": 100 | NUMBER(38,0) |
| "price": 19.99 | NUMBER(10,2) |
| "rate": 1.234e-7 | FLOAT |
| "flag": true | BOOLEAN |
| "day": "2024-03-15" | DATE |
| "ts": "2024-03-15 09:30:00" | TIMESTAMP_NTZ |
| "ts": "2024-03-15T09:30:00+02:00" | TIMESTAMP_TZ |
| "meta": { ... } | VARIANT |
[
{"order_id": 1, "qty": 3, "price": 19.99, "placed_at": "2024-03-15 14:00:00"},
{"order_id": 2, "qty": 1, "price": 99.00, "placed_at": "2024-03-15 14:05:22"}
]
CREATE TABLE orders (
order_id NUMBER(38,0) NOT NULL,
qty NUMBER(38,0) NOT NULL,
price NUMBER(10,2) NOT NULL,
placed_at TIMESTAMP_NTZ NOT NULL
);
No signup, no install — runs entirely in your browser.
Open the Schema Inferrer →