Want to migrate from Redshift to SQL Server ?
Try Withdata DBCopier, a Redshift to SQL Server converter for Windows, Mac, and Linux, Migrate Redshift to SQL Server, Easy and Fast.
- Step by Step, just a few mouse clicks.
- Create SQL Server tables with auto mapping data types. Create SQL Server indexes.
Migrate from Redshift to SQL Server
Login to Redshift -> Login to SQL Server -> Select tables to migrate -> Migrate from Redshift to SQL Server
Choose source Redshift database and logon.
Choose target SQL Server database and logon.
Click “Wizard – Import All Tables” at task dialog.
then show the wizard.
1. Open source Redshift.
2. Set “Import Type”.
3. Select SQL Server tables to migrate.
4. Migrate from Redshift to SQL Server.
Create SQL Server tables. Copy Redshift data to SQL Server. Create SQL Server indexes.
FAQ
More about Redshift to SQL Server converter
Download Withdata DBCopier
See also:
Redshift → SQL Server reference
Type mapping
| Value kind | in Redshift | in SQL Server |
|---|---|---|
| Int | integer | int |
| Decimal | numeric(p,s) | decimal(p,s) |
| Float | double precision | float |
| Text | varchar(n) | nvarchar(n) |
| Long text | varchar(max) | nvarchar(max) |
| Datetime | timestamp | datetime2 |
| Binary | (none) | varbinary(max) |
| Boolean | boolean | bit |
| JSON | super | nvarchar(max) |
Dialect differences
Both Redshift and SQL Server are database servers, so the differences below are dialect-level: the same concept is spelled differently on each side.
| Property | in Redshift | in SQL Server |
|---|---|---|
| port | 5439 | 1433 |
| identifiers | "double quotes" | [square brackets] |
| row limit | LIMIT n | SELECT TOP n |
| dates | timestamp, date | datetime, datetime2, date, time |
| long text | VARCHAR(MAX) | nvarchar(max) |
| binary | — | varbinary(max) |
Command line
| Side | Command |
|---|---|
| Redshift | UNLOAD to S3 |
| SQL Server | bcp |
| SQL Server (load) | bcp, or BULK INSERT |
| Redshift (load) | COPY from S3 |
No counterpart
- SQL Server has no equivalent for Binary – it has to be flattened or dropped.
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