Withdata Software

Export FoxPro query results to SQL

Want to export data from FoxPro query to SQL file?

Try Withdata DBToFile, a FoxPro to SQL converter for Windows, Linux, and macOS, Export FoxPro data to SQL, Easy and Fast.

Download Withdata DBToFile
Windows 64 bit
Windows 32 bit
Linux .deb (For Debian, Ubuntu) 64 bit
Linux .rpm (For Red Hat, Fedora, SUSE) 64 bit
MacOS 64 bit

Export data from FoxPro query to SQL file

Login to FoxPro -> Enter FoxPro query -> Set SQL file options -> Export FoxPro query to SQL

Choose FoxPro and logon.

Click “Export From Query” at task dialog.

Select SQL file type.

1. Enter FoxPro query.

2. Set SQL file options.

3. Set rows options.

4. Export FoxPro query results to SQL file.

After exporting, you can view output SQL files.


More about FoxPro to SQL converter

See also:

FoxPro → SQL reference

Type mapping

Value kindin FoxProin SQL
IntNumeric(10,0)INT
BigintNumeric(19,0)BIGINT
DecimalNumeric(p,s)DECIMAL(p,s)
FloatFloatDOUBLE PRECISION
TextCharacter(n)VARCHAR(n)
Long textMemoTEXT / CLOB
DateDateDATE
Datetime(none)TIMESTAMP
BinaryGeneralBLOB / BYTEA
BooleanLogicalBOOLEAN / SMALLINT
JSON(none)JSON / TEXT

Dialect differences

FoxPro is a database server and SQL is a file format, so the gap is wider than a dialect difference - the rows below are where values and structure stop lining up.

Propertyin FoxProin SQL
port(file-based)—
identifiers—Two competing conventions: single-quoted literals and diale...
row limit(driver dependent)—
datesDate (D)Depends on the dialect: DATE literals, TO_DATE(), or plain ...
long textMemo (M)—
binaryGeneral (G)Dialect-specific: X-quoted literal, 0x hex, or decode()
separator—Statement terminators (;)
encoding—No declaration
typing—Types belong to the target database, and they differ betwee...
shapeTables of rows and columnsStatements; a dump usually means CREATE TABLE plus INSERT rows
ceiling—No formal limit, but a single INSERT statement has to fit i...

No counterpart

  • SQL has no equivalent for Date and time - it has to be flattened or dropped.
  • SQL has no equivalent for JSON - it has to be flattened or dropped.

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