---
title: Data Transfer
description: Move table data between connections or database engines.
---

Data Transfer copies table data from one connection to another. Use it for development, testing, migration, and consolidation workflows. It is not a replacement for a production-grade replication pipeline.

## Use Cases

- Copy part of production data into a development environment
- Move data between engines such as MySQL, PostgreSQL, SQLite, and SQL Server
- Consolidate multiple sources into an analysis database
- Prepare reproducible datasets for testing

<Callout type="warn">
Cross-engine transfer involves type mapping, defaults, constraints, and auto-increment differences. Validate transferred data afterward, and rehearse important migrations in a test environment first.
</Callout>

## Workflow

<Steps>
  <Step>
    ### Select the Source

    The source connection is where data is read from. Confirm the account can read the selected tables.
  </Step>
  <Step>
    ### Select the Target

    The target connection is where data is written. Confirm write permissions and verify the target environment.
  </Step>
  <Step>
    ### Choose Tables

    Transfer all tables or select only the tables you need. For large tables, consider transferring in smaller batches.
  </Step>
  <Step>
    ### Start Transfer

    DBX reads rows table by table and writes them to the target database using the selected mode. You can also choose whether target tables should be created.
  </Step>
  <Step>
    ### Check Results

    After transfer, inspect row counts, errors, and key fields.
  </Step>
</Steps>

## During Transfer

DBX shows:

- Current table
- Rows transferred
- Overall progress
- Errors and the table that caused each error

If a table fails, the current transfer stops and shows the error. Fix the structure, permission, or constraint issue, then start the transfer again.

## Transfer Options

| Option | Details |
|---|---|
| Create target table | Try to create the target table from the source structure when it does not exist |
| Append | Insert data after existing target rows |
| Overwrite | Clear the target table before writing source rows |
| Upsert | Use key-aware write behavior where the target database path supports it |
| Batch size | Control how many rows are written per batch |

## Database Coverage

SQL-based transfer is available for MySQL, PostgreSQL, SQLite, SQL Server, Oracle, ClickHouse, DuckDB, DM, and GaussDB. Cross-engine transfers use DBX's type mapping layer, so always verify row counts and important column values after transfer.

## Before You Transfer

| Check | Why It Matters |
|---|---|
| Target environment | Avoid writing to the wrong database |
| Table structure | Field names, types, primary keys, and unique constraints affect inserts |
| Data volume | Large tables may take longer or hit timeouts |
| Constraints | Foreign keys, unique constraints, and NOT NULL fields may fail writes |
| Sensitive data | Production data may need masking before copying into lower environments |

## Related Features

<Cards>
  <Card title="Table Import" href="/en/docs/table-import">
    Import CSV, TSV, JSON, or Excel into a single table.
  </Card>
  <Card title="Database Export" href="/en/docs/database-export">
    Export a database as SQL for backup or offline migration.
  </Card>
</Cards>