> AI agents: this is one page from Mammoth Analytics documentation. The index of all pages as Markdown is https://mammoth.io/docs/llms.txt. Append `.md` to any docs URL, or send `Accept: text/markdown`, to get Markdown.

# Choose how a database dataset refreshes in Mammoth

> Pick what each refresh does to a Mammoth database dataset: replace all rows, add only new rows by a key column, or keep only the newest, and change it later.
>
> Applies to: Where: Data → Connections › connector workspace › Save as dataset › On each refresh

When you save a database query as a dataset, you choose when it refreshes and what each refresh does: replace every row, or add only new rows told apart by a key column. You set this in the **Save as a dataset** dialog of the connector workspace, after [querying the database](https://mammoth.io/docs/learn/get-data-in/query-a-database/), and can change it later in the dataset's settings.

## Choose what happens on each refresh

1. Click **Save as dataset** when the rows look right.
2. In **Save as a dataset**, enter a **Name** and pick a folder.
3. Under **Keep it up to date**, choose **Daily at 06:00** or **Only when I ask**.
4. The dialog states what each refresh does. Click **Change** to pick another option under **On each refresh** (see the table below).
5. For **Add only new rows** and **Keep only the newest rows**, pick a **Key column**: a column whose values only ever go up, like an ID or a date.
6. Click **Save as dataset**.

| Option | What it does | When to use |
| --- | --- | --- |
| **Replace all rows** | Matches the source after every refresh | Most tables, lookups and snapshots |
| **Add only new rows** | Keeps what you have and adds rows that are new, told apart by a key column | Building up history from a table that only grows |
| **Add every row again** | Adds a full copy of the query result on each refresh. Shown when the result has no column that can serve as a key. | Rare: when you want a copy per refresh |
| **Keep only the newest rows** | Empties the dataset, then brings in rows since the last refresh. Needs a key column. | Keeping only the latest batch |

Without a key column, **Add only new rows** brings in a full copy each time, and **Keep only the newest rows** can't be saved.

Choosing **Daily at 06:00** also creates a [Dataset Refresh](https://mammoth.io/docs/learn/automate/refresh-a-dataset/) automation for the dataset, with its first run the next morning.

### Worked example: keep a growing orders table up to date

Your `orders` table only ever gets new rows, and `order_id` always goes up. Choose **Daily at 06:00**, then **Add only new rows** with **Key column** `order_id`. Each morning Mammoth adds only orders with an ID above the last one it imported.

## Change the update method after saving

A saved connector dataset has an **Update method** you can change later from the dataset's settings (see [Dataset settings and history](https://mammoth.io/docs/learn/organise/dataset-settings/)). The change applies from the next refresh; your current data stays as it is until then.

For connectors that support a key column (including PostgreSQL, MySQL, SQL Server, Amazon Redshift, Snowflake, Google BigQuery, Databricks, Apache Hadoop and MongoDB):

| Option | What it does |
| --- | --- |
| **Replace all data** | Rebuilds the dataset on every refresh, so it always matches the source |
| **Add new rows only** | Each refresh adds the rows that appeared since the last one, using a **Key column** |
| **Keep only the newest rows** | Each refresh empties the dataset and brings in only the rows since the last one |

For connectors whose refresh doesn't use a key column, including SAP HANA, Oracle Database, Microsoft Dynamics, Monday.com, NetSuite and Google Ads, the options are **Replace all data** and **Add to existing data**, which adds every row it brings in.

With a key column, only rows above the last value are imported. Rows changed or deleted at the source afterwards are not updated in Mammoth.

## Related

- [Query a database and choose how it refreshes](https://mammoth.io/docs/learn/get-data-in/query-a-database/): write the query you save.
- [Refresh a dataset](https://mammoth.io/docs/learn/automate/refresh-a-dataset/): schedule refreshes.
- [Batches: see and fix what arrived](https://mammoth.io/docs/learn/get-data-in/batches/): each refresh adds or replaces batches.
- [Speed up pipelines and connectors](https://mammoth.io/docs/learn/help/performance/): incremental refresh and query filtering.

---
Source: https://mammoth.io/docs/learn/get-data-in/database-refresh-options.md · Updated: 2026-11-08