About

Converting JavaScript objects to SQL statements by hand introduces transcription errors. A misquoted string or a missing comma in an INSERT statement causes silent data corruption or runtime failures that propagate through your database layer. This tool parses raw JS object literals and arrays, infers column names from object keys, escapes values according to SQL standards (single-quote doubling, NULL handling, boolean mapping), and outputs syntactically valid queries for INSERT, SELECT, UPDATE, DELETE, and CREATE TABLE operations. It handles batch arrays by generating multi-row inserts or repeated statements.

Type inference follows deterministic rules: JavaScript number maps to INTEGER or FLOAT depending on whether the value contains a decimal point. Strings map to VARCHAR(255). Booleans map to BOOLEAN. NULL and undefined both produce SQL NULL. The tool assumes a flat object structure. Nested objects and arrays are serialized to JSON strings. Pro tip: always review generated WHERE clauses before executing UPDATE or DELETE queries against production databases.

Formulas

The conversion follows a deterministic mapping pipeline from JavaScript object structure to SQL syntax.

INSERT INTO tableName (key₁, key₂, ..., key_n) VALUES (escape(val₁), escape(val₂), ..., escape(val_n))

Where key_i = Object.keys(obj)[i] and val_i = obj[key_i].

escape(v) =

{

NULL if v ≡ null ∨ undefined ∨ NaNv if typeof v = "number" ∧ isFinite(v)TRUE/FALSE if typeof v = "boolean"'replace(v, "'", "''")' if typeof v = "string""JSON.stringify(v)" otherwise

For CREATE TABLE, the type inference function inferType(v) maps: string → VARCHAR(255), integer → INTEGER (or BIGINT if v > 2147483647), float → FLOAT, boolean → BOOLEAN, object/array → TEXT, null → TEXT. Column names are extracted via Object.keys and sanitized to allow only alphanumeric characters and underscores.

Reference Data

JS Type	SQL Type (Inferred)	Example JS Value	Example SQL Output	Notes
string	VARCHAR(255)	"hello"	"hello"	Single quotes escaped by doubling
number (integer)	INTEGER	42	42	No quotes around numeric literals
number (float)	FLOAT	3.14	3.14	Decimal point triggers FLOAT inference
boolean	BOOLEAN	TRUE	TRUE	Mapped directly to SQL boolean
null	NULL	null	NULL	No quotes, literal NULL keyword
undefined	NULL	undefined	NULL	Treated identically to null
object (nested)	TEXT	{a: 1}	"{"a":1}"	JSON-serialized, stored as TEXT
Array	TEXT	[1, 2]	"[1,2]"	JSON-serialized, stored as TEXT
Date (string)	VARCHAR(255)	"2024-01-15"	"2024-01-15"	Date strings treated as VARCHAR
Empty string	VARCHAR(255)	""	''	Valid empty string, not NULL
NaN	NULL	NaN	NULL	Non-numeric mapped to NULL
Infinity	NULL	Infinity	NULL	Non-finite mapped to NULL
String with quotes	VARCHAR(255)	"O'Brien"	'O''Brien'	Single quote doubled for SQL safety
Multiline string	TEXT	"line1\nline2"	"line1\nline2"	Newlines preserved in value
Large integer	BIGINT	9007199254740991	9007199254740991	Values > 2147483647 use BIGINT

Frequently Asked Questions

Nested objects and arrays are serialized using JSON.stringify and stored as SQL string literals with type TEXT. For example, { address: { city: "NYC" } } produces the value "{"city":"NYC"}". If you need relational normalization (separate tables for nested entities), you must restructure the input manually into flat objects before conversion.

The converter escapes single quotes by doubling them (O'Brien becomes O''Brien), which is the standard SQL escaping mechanism. However, this tool generates static SQL statements for development, migration scripts, and testing. For production application code, always use parameterized queries or prepared statements provided by your database driver, never string-concatenated SQL.

For CREATE TABLE, the converter examines the first non-null value encountered for each key across all objects in the array. If the first object has age: 25 (INTEGER) but the second has age: "unknown" (VARCHAR), the column type will be INTEGER based on first occurrence. Review the generated schema and adjust types manually for inconsistent datasets.

Yes. The table name input field accepts any valid SQL identifier. The converter sanitizes the name to allow only alphanumeric characters, underscores, and dots (for schema-qualified names like schema.table). If left blank, it defaults to "my_table".

Properties with undefined values are treated identically to null. They produce SQL NULL in INSERT/UPDATE statements. In CREATE TABLE, if a key has only undefined values across all objects, the column type defaults to TEXT. Note that JSON.stringify omits undefined properties entirely, but this converter explicitly handles them before serialization.

The converter uses the first key of the object as the WHERE condition by default (typically an "id" field). You can select which key to use as the WHERE clause identifier from the dropdown that appears when UPDATE or DELETE mode is selected. All remaining keys become SET assignments in UPDATE queries.