---
title: "AWS Aurora - Xata"
description: "Learn how to migrate your AWS Aurora PostgreSQL database to Xata using xata clone"
source: "https://xata.io/docs/migrations/aws-aurora"
---

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## ​Prerequisites

- AWS Aurora PostgreSQL cluster
- Access to AWS Console
- Xata account and project setup with a running `main` branch
- Network access to your Aurora cluster

## ​Install and configure the Xata CLI

Install the Xata CLI:

```
curl -fsSL https://xata.io/install.sh | bash
```

Authenticate with your Xata account:

```
xata auth login
```

## ​Find the Aurora connection string

Aurora connection strings typically look something like this:

```
postgresql://your_username:your_password@aurora-endpoint:5432/dbname
```

You can find the aurora-endpoint in the AWS RDS Console under “Connectivity & security”.

Tip

Don’t have a live connection, or prefer to export a snapshot to Amazon S3? You can also migrate from [Parquet files](/docs/migrations/parquet) exported to S3.

## ​Initialize Xata project

Go to a local folder that you want to save the Xata configuration to and initialize it like this:

```
xata init
```

Select your organization and project you want to use. For the database name you can either choose a new one (e.g `xata`) or use the same that you have in Aurora. If the database doesn’t exist, it will be created. In case you need to redo this step, you can reset the configuration by deleting the `.xata/project.json` file and running `xata init` again.

## ​Start the migration

Begin the data transfer:

```
xata clone start --validation-mode relaxed --source-url '<<aurora-connection-string>>'
```

Depending on how large the source database is, this step might take a while. A progress bar will show you the progress in the CLI.

## ​Verification

After migration, verify your data:

1. **Connect to Xata Branch**:

   ```
   psql `xata branch url`
   ```

2. **Check Data Integrity**:

   ```
   -- List tables
   \dt

   -- Compare row counts
   SELECT COUNT(*) FROM your_table;

   -- Check sample data
   SELECT * FROM your_table LIMIT 10;
   ```

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