---
schema_version: "1"
id: debe1866938caf0168b9b8520425d88accf833ed6cc8ff1a0155984da905a01f
title: Caching or Acceleration in Data Federation
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/data/264-0-0/c360_a_accelerated_data_lake_objects.md
canonical_url: https://help.salesforce.com/s/articleView?id=data.c360_a_accelerated_data_lake_objects.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: 1a497e08aa427208355ba9375cdff8d8a19ee3930c2f442fc0f4a60456ebc4cc
description: Caching retrieves data from the external source and temporarily stores it in a data lake object in Data 360. When you enable acceleration while creating a data stream, you turn on caching. We recommend caching when accessing large data sets or when data changes frequently. You can refresh the cached data at your preferred frequency.
products:
  - Data 360
release: "264"
---
# Caching or Acceleration in Data Federation

Caching retrieves data from the external source and temporarily stores it in a data lake object in Data 360. When you enable acceleration while creating a data stream, you turn on caching. We recommend caching when accessing large data sets or when data changes frequently. You can refresh the cached data at your preferred frequency.

Caching is turned off by default when you create a data stream, but you can edit the data stream and enable or disable it at any time. You can incrementally refresh all objects with a datetime field as frequently as every 15 minutes. An incremental refresh updates the cached object with data that was added or changed since the last refresh, but it doesn’t update deleted data. If the refresh frequency is 24 hours or more, you can then select the time and day.

To enable incremental refresh, select **Edit Data Stream** after deploying a new data stream, select the desired record modified field, which denotes the timestamp for the incremental refresh, and the desired frequency. If the selected frequency is greater than or equal to 24 hours, you can then choose a desired refresh time and day. Incremental refresh currently supports upserts and doesn't support deletes. The cached object is updated with data added or changed since the last refresh. If you don't edit the data stream type, the cache refreshes fully each time.

You can also retrieve data in full refresh mode. If you opt for a full refresh, during each refresh cycle, all the existing cached data is deleted and replaced with the new dataset. To keep your data current and in sync with your data source, perform a full refresh at regular intervals. Enabling acceleration impacts the consumption of credits used for billing. When acceleration is enabled, ingesting data into the cache consumes credits in the Batch Data Pipeline usage type.

Accelerated queries consume credits at a different rate and multipliers than live queries. To learn more, see [Billing Considerations for Data Federation](https://help.salesforce.com/s/articleView?id=data.c360_a_billing_considerations_for_data_federation.htm&release=264.0.0&type=5 "Data Federation uses Data 360 to query and activate external warehouse data without copying it. Use of Data Federation impacts the consumption of credits in these usage types.").

![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/images/icon_note.png)

Note Snowflake connector supports the Unload function, which enhances acceleration rates using a Snowflake initiated staging bucket. This is turn on by default, but you can turn it off by editing the connection.

#### See Also

- [_Salesforce Help_: Zero Copy Data Federation](https://help.salesforce.com/s/articleView?id=data.c360_a_byol_data_federation.htm&release=264.0.0&type=5 "The Data 360 zero copy data federation is the process of querying data from multiple, physically distinct data sources. This approch allows users to treat disparate systems as a single logical system, called a federation, while maintaining the autonomy of each system. Importantly, data federation avoids duplicating data across system boundaries. Data 360.")