> For the complete documentation index, see [llms.txt](https://daton-sarasanalytics.gitbook.io/daton/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://daton-sarasanalytics.gitbook.io/daton/platform/features/data/data-type-mapping.md).

# Data Type Mapping

Mapping data types is an important aspect of any data replication product, and it is not any different with Daton. Fortunately, Daton handles all the data type mapping for you so that you don't have to worry about which source data type maps to which destination data type regardless of which data destination you choose.

Daton supports a multiple of sources ranging from SaaS applications like Google Analytics, Facebook Ads, Zendesk, FreshDesk, Salesforce to databases like Oracle, MySQL, PostgreSQL, and many others. Some of these systems are built on traditional relational databases while some others rely on NoSQL databases to store data. When Daton retrieves this data, it has to take a decision on how data types from these sources have to be mapped to the destination or data warehouse of your choice.

This guide gives you a detailed account on how data types are handled in Daton for various data warehouses.

### Source to Oracle Autonomous Data Warehouse Mapping

### Source to BigQuery Mapping

BigQuery is on of the born in the cloud data data warehouses specialized for running analytics workloads.

| Source Data Type |   |   |
| ---------------- | - | - |
|                  |   |   |
|                  |   |   |
|                  |   |   |
|                  |   |   |
|                  |   |   |
|                  |   |   |
|                  |   |   |

### Source to AWS Redshift Mapping

### Source to PostgreSQL Mapping

### Source to MySQL Mapping


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