Want to bulk import JSON files into Redshift tables at one time?
Try Withdata FileToDB, a desktop JSON to Redshift converter for Windows, MacOS, and Linux, Batch import JSON to Redshift, 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.
- Support Windows, Linux, and macOS.
Download Withdata FileToDB
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Linux .deb (For Debian, Ubuntu) 64 bit
Linux .rpm (For Red Hat, Fedora, SUSE) 64 bit
MacOS 64 bit
Bulk import JSON files into Redshift tables
Login to Redshift -> Choose JSON files -> Set Redshift tables -> Import JSON files to Redshift tables
Choose Redshift and logon.
Click “Wizard – N Files To N Tables” at task dialog.
Select the “JSON” file type.
then show the wizard.
1. Select a folder that constains JSON files.
2. Config first JSON file importing options.
3. Set “Import Type”.
4. Map Redshift tables to JSON files.
5. Summary. Set “Convert Rows” and “Skip Rows” if need.
6. Import JSON files to Redshift tables, 1 file to 1 table, one by one.
View imported data in Redshift table
Bulk import JSON files into Redshift tables in command line
Save “bulk JSON files to Redshift tables” session, then you can:
- Bulk import JSON files into Redshift tables in Windows command line.
- Bulk import JSON files into Redshift tables in Linux command line.
- Bulk import JSON files into Redshift tables in macOS command line.
Set scheduled tasks for bulk importing JSON files into Redshift tables
You can schedule and automate this converting task by:
- Save session and create .bat (Windows) or .sh (Linux/macOS) file for “JSON to Redshift” conversion.
- Set scheduled task for “JSON to Redshift” conversion.
FAQ
More about Withdata FileToDB – JSON to Redshift 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
See also:
JSON → Redshift reference
Type mapping
| Value kind | in JSON | in Redshift |
|---|---|---|
| Int | 1234 (number) | integer |
| Bigint | 9007199254740993 | bigint |
| Decimal | 1234.56 (number) | numeric(p,s) |
| Float | 1.234e10 (number) | double precision |
| Text | "text" (string) | varchar(n) |
| Long text | "multi-line\ntext" (escaped newline inside a string) | varchar(max) |
| Date | "2026-09-18" (string) | date |
| Datetime | "2026-09-18T14:30:00Z" (string) | timestamp |
| Binary | "base64:..." (string) | (none) |
| Boolean | true / false (boolean) | boolean |
| JSON | nested object or array, kept as structure | super |
Dialect differences
JSON is a file format and Redshift 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 | in Redshift |
|---|---|---|
| port | — | 5439 |
| identifiers | Double quotes; backslash escapes | "double quotes" |
| row limit | — | LIMIT n |
| dates | No date type: dates arrive as strings and the reader must p... | timestamp, date |
| long text | — | VARCHAR(MAX) |
| 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 | — |
Command line
| Side | Command |
|---|---|
| Redshift | UNLOAD to S3 |
| Redshift (load) | COPY from S3 |
No counterpart
- JSON values of kind Binary have nowhere to go in Redshift.
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