> For the complete documentation index, see [llms.txt](https://docs.tonic.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tonic.ai/app/setting-up-your-database/mongodb/mongodb-tonic-differences.md).

# Structural differences and limitations with MongoDB

The data structure for MongoDB is different from that of relational data connectors.

Instead of schemas, tables, and columns, a MongoDB database consists of collections and fields. A field might be an object that is made up of other fields. In other words, a collection can have a tree structure that is similar to a JSON document.

For workspaces that use MongoDB, the Tonic Structural application has the following differences.

## Terminology changes <a href="#mongodb-tonic-differences-terminology" id="mongodb-tonic-differences-terminology"></a>

On the following Structural views, the term "collection" replaces the term "table".

* [Privacy Hub](/app/generation/privacy-hub.md)
* [Schema Changes](/app/generation/schema-changes.md)
* [Subsetting](/app/generation/subsetting.md)

References to columns are also replaced:

* On **Privacy Hub**, the protection status panels refer to "fields" instead of "columns".
* On the **Schema Changes** view, the change lists refer to "paths" instead of "columns".

## No schema caching

MongoDB does not allow you to cache the database schema.

## Privacy Hub - Latest Collection Scan <a href="#mongodb-tonic-differences-privacy-hub-collection-scan" id="mongodb-tonic-differences-privacy-hub-collection-scan"></a>

For MongoDB workspaces, Structural must scan each collection to determine the fields and data types within that collection. Until a scan is performed, you cannot configure the collection modes and generators.

For MongoDB workspaces, **Privacy Hub** includes an additional **Latest Collection Scan** section that shows the most recent time that a scan was performed on each scanned collection.

For more information, go to [Performing scans on collections](/app/generation/working-with-document-based-data/mongodb-collection-scans.md).

## No Privacy Report downloads

For MongoDB workspaces, there are no options to download a Privacy Report CSV or PDF.

## No workspace inheritance <a href="#mongodb-tonic-differences-workspace-inheritance" id="mongodb-tonic-differences-workspace-inheritance"></a>

MongoDB workspaces do not support workspace inheritance.

## Collection View replaces Database View and Table View <a href="#mongodb-tonic-differences-collection-view" id="mongodb-tonic-differences-collection-view"></a>

For MongoDB workspaces, there is no **Database View** or **Table View**. Instead, MongoDB workspaces have a **Collection View**.

This view allows you to perform the same functions as **Table View**, but the display is more like **Database View**. For more information, go to [Using Collection View](/app/generation/working-with-document-based-data/mongodb-collection-view.md).

## Collection mode (table mode) limitations <a href="#mongodb-tonic-differences-collection-modes" id="mongodb-tonic-differences-collection-modes"></a>

Collection mode is the term for [table mode](/app/generation/table-modes.md) in MongoDB workspaces.

MongoDB only supports De-Identify, Truncate, and Preserve Destination modes.

## Generator limitations <a href="#mongodb-tonic-differences-generators" id="mongodb-tonic-differences-generators"></a>

MongoDB workspaces cannot use the following generators:

* Algebraic
* Alphanumeric Key
* Array Character Scramble
* Array JSON Mask
* Array Regex Mask
* Cross-Table Sum
* CSV Mask
* Event Timestamps
* HTML Mask
* JSON Mask
* SIN
* Text Composition
* URL

## Self-consistency only

MongoDB workspaces only support self-consistency.  You cannot configure a MongoDB field to be consistent with another field.

## No upsert <a href="#mongodb-limitations-no-upsert" id="mongodb-limitations-no-upsert"></a>

MongoDB workspaces do not support upsert.

## No output to a container repository <a href="#mongodb-tonic-limitations-containerization" id="mongodb-tonic-limitations-containerization"></a>

For MongoDB workspaces, you cannot write the destination data to a container repository.

## No post-job scripts <a href="#mongodb-tonic-differences-post-job-scripts" id="mongodb-tonic-differences-post-job-scripts"></a>

For MongoDB workspaces, there is no option to run post-job scripts after a job.

You can create [webhooks](/app/workflows/webhooks.md) that are triggered by data generation jobs.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.tonic.ai/app/setting-up-your-database/mongodb/mongodb-tonic-differences.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.