Want to import data from JSON array to Clipper?
Try Withdata FileToDB, a desktop JSON array to Clipper converter for Windows, MacOS, and Linux, Import JSON array to Clipper, Easy and Fast.
- Can run in GUI mode, Step by Step, just a few mouse clicks.
- Can run in Command line, for Scheduled Tasks and Streams.
- Convert locally and privately, avoid uploading large or private JSON file(s) to online services.
Download Withdata FileToDB
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
Import data from JSON array to Clipper
Login to Clipper -> Choose JSON array file -> Set Clipper table -> Import JSON array to Clipper
Choose Clipper and logon.
Click “Wizard – 1 File To 1 Table” at task dialog.
Select the “JSON” file type.
then show the wizard.
1. Open a JSON array file.
Support large ( > 4GB ) JSON array file.
Here is the file’s content.
FileToDB will parse JSON array.
2. Select a Clipper table and config fields.
3. Preview data will be in Clipper table.
4. Import JSON array data to Clipper.
View imported data in Clipper table
Convert JSON array to Clipper in command line
Save “JSON array to Clipper” session, then you can:
- Import JSON array to Clipper in Windows command line.
- Import JSON array to Clipper in Linux command line.
- Import JSON array to Clipper in macOS command line.
Set scheduled tasks for converting JSON array to Clipper
You can schedule and automate this “JSON array to Clipper” conversion task by:
- Save session and create .bat (Windows) or .sh (Linux/macOS) file for “JSON array to Clipper” conversion.
- Set scheduled task for “JSON array to Clipper” conversion.
FAQ
More about Withdata FileToDB – JSON Array to Clipper converter
Download Withdata FileToDB
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
JSON Array → Clipper reference
Type mapping
| Value kind | in JSON Array | in Clipper |
|---|---|---|
| Int | 1234 (number) | Numeric(10,0) |
| Bigint | 9007199254740993 | Numeric(19,0) |
| Decimal | 1234.56 (number) | Numeric(p,s) |
| Float | 1.234e10 (number) | Float |
| Text | "text" (string) | Character(n) |
| Long text | "multi-line\ntext" (escaped newline inside a string) | Memo |
| Date | "2026-09-18" (string) | Date |
| Datetime | "2026-09-18T14:30:00Z" (string) | (none) |
| Binary | "base64:..." (string) | (none) |
| Boolean | true / false (boolean) | Logical |
| JSON | nested object or array, kept as structure | (none) |
Dialect differences
JSON Array is a file format and Clipper is a database server, so the target has to be told the types the file never carried - the rows below are where the two sides diverge.
| Property | in JSON Array | in Clipper |
|---|---|---|
| port | — | (file-based) |
| identifiers | Double quotes; backslash escapes | — |
| row limit | — | (driver dependent) |
| dates | No date type: dates arrive as strings and the reader must p... | Date (D) |
| long text | — | Memo (M) |
| binary | Not supported natively - base64 inside a string | — |
| separator | Braces and commas | — |
| encoding | UTF-8 by definition | — |
| typing | string, number, boolean, null, object, array - no date type | — |
| shape | Nested objects and arrays | Tables of rows and columns |
| ceiling | Whole document is usually parsed into memory | — |
No counterpart
- JSON Array values of kind Date and time have nowhere to go in Clipper.
- JSON Array values of kind Binary have nowhere to go in Clipper.
- JSON Array values of kind JSON have nowhere to go in Clipper.
Convert your data online, free
Free in-browser converters for CSV, Excel, JSON, XML and SQL: Withdata Online Data Conversion. Large files, batch conversion or scheduling? See the offline desktop apps, or browse all data conversion tools.