Merge multiple similar dBase tables to 1 Access table

Want to transfer data from multiple similar dBase tables to 1 Access table?

Try Withdata DBCopier, a dBase to Access converter for Windows, Mac, and Linux, Copy dBase data to Access, 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.
• Support Windows, Linux, and macOS.

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Linux .deb (For Debian, Ubuntu) 64 bit
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MacOS 64 bit

Transfer data from multiple similar dBase tables to a single Access table

Login to dBase and Access -> Select source dBase tables -> Set the target Access table -> Copy dBase data to Access

Choose source dBase database and logon.

Choose target Access database and logon.

Click “Convert Similar Tables” at task dialog.

then show the wizard.

1. Select similar dBase tables.

2. Select a destination Access table and config fields.

3. Preview data.

4. Import data from multiple similar dBase tables to a single Access table.

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More about dBase to Access converter

See also:

• Copy dBase table data to Access
• Copy dBase query results to Access table
• Batch copy dBase tables to Access

dBase → Access reference

Type mapping

Value kind	in dBase	in Access
Int	Numeric(10,0)	Long Integer
Bigint	Numeric(19,0)	Long Integer
Decimal	Numeric(p,s)	Decimal
Float	Float	Double
Text	Character(n)	Text(n)
Long text	Memo	Long Text
Date	Date	Date/Time
Datetime	(none)	Date/Time
Binary	(none)	OLE Object
Boolean	Logical	Yes/No
JSON	(none)	Long Text

Dialect differences

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

Property	in dBase	in Access
identifiers	—	[square brackets]
row limit	(driver dependent)	SELECT TOP n
dates	Date (D)	Date/Time
long text	Memo (M)	MEMO
binary	—	OLE Object

No counterpart

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

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