Data retention policy
Databricks retains the personal information described in this Privacy Notice for as long as you use our Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.
Data archiving and removal policy
Data Deletion
- During Use. The Platform Services provide Customer with functionality that permit Customer to delete Customer Content under Databricks’ control.
- Upon Workspace Cancellation. Customer Content contained within a Customer Workspace is permanently deleted within thirty (30) days following cancellation of the Workspace.
https://www.databricks.com/legal/security-addendum Data storage policy
Data Storage. Depending on your configuration and which Platform Services features a Customer accesses, Databricks may process Customer Content stored within Customer's own Cloud Service Provider account and/or within Databricks' infrastructure. See the Documentation for details: https://docs.databricks.com/aws/en App/service has sub-processors
yes
Guidelines for sub-processors
App/service uses large language models (LLM)
yes
LLM model(s) used
If the partner-powered AI features setting is enabled, Databricks AI assistive features use models hosted by Azure OpenAI service or Anthropic on Databricks. If disabled the some AI assistive features may use a Databricks-hosted model.
LLM retention settings
Your data remains confidential. Databricks does not train generative foundation models with data you submit to these features.
Our model partners do not retain data you submit through these features, even for abuse monitoring.
LLM data tenancy policy
Databricks only uses the data necessary to provide the service. Data is sent only when you interact with Databricks AI assistive features. All access is governed by Unity Catalog.
LLM data residency policy