Batch copy Clipper tables to Azure

Want to batch copy data from Clipper tables to Azure?

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Batch copy data from Clipper tables to Azure tables

Login to Clipper and Azure -> Select source Clipper tables -> Set target Azure tables -> Copy Clipper data to Azure

Choose source Clipper database and logon.

convert Clipper data to Azure data - Choose Clipper and logon

Choose target Azure database and logon.

convert Clipper data to Azure data - Choose Azure and logon

Click “Convert All Tables” at task dialog.

Batch import data from Clipper tables to Azure tables - Task Window

then show the wizard.

1. Select source Clipper tables.

Batch convert data from Clipper tables to Azure tables - Open Source schema

2. List target Azure tables.

Batch extract data from Clipper tables to Azure tables - select destination schema

3. Select Azure tables to import.

Batch import data from Clipper tables to Azure tables - select tables

4. Transfer data from Clipper tables to Azure.

Batch copy data from Clipper tables to Azure tables - batch import


More about Clipper to Azure converter

See also:

Clipper → Azure SQL reference

Type mapping

Value kindin Clipperin Azure SQL
IntNumeric(10,0)int
BigintNumeric(19,0)bigint
DecimalNumeric(p,s)decimal(p,s)
FloatFloatfloat
TextCharacter(n)nvarchar(n)
Long textMemonvarchar(max)
DateDatedate
Datetime(none)datetime2
Binary(none)varbinary(max)
BooleanLogicalbit
JSON(none)nvarchar(max)

Dialect differences

Both Clipper and Azure SQL are database servers, so the differences below are dialect-level: the same concept is spelled differently on each side.

Propertyin Clipperin Azure SQL
port(file-based)1433
identifiers—[square brackets]
row limit(driver dependent)SELECT TOP n
datesDate (D)datetime2, date, time
long textMemo (M)nvarchar(max)
binary—varbinary(max)

Command line

SideCommand
Azure SQLbcp
Azure SQL (load)bcp, or BULK INSERT

No counterpart

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

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