> 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/generation/generators/generator-reference/address.md). # Address Generates a random mailing address-like string. You can indicate which part of an address string that the column contains. For example, the column might contain only the street address or the city, or it might contain the full address. ## Characteristics


Consistency	Yes, can be made self-consistent or consistent with another column.
Linking	Yes, can be linked.
Differential privacy	Yes, if consistency is not enabled.
Data-free	Yes, if consistency is not enabled.
Allowed for primary keys	No
Allowed for unique columns	No
Uses format-preserving encryption (FPE)	No
Privacy ranking	1 if not consistent 4 if consistent
Generator ID (for the API)	`AddressGenerator`

## How to configure ### Linking to other columns From the **Link To** dropdown list, select the columns to link this column to. You can link columns that use the Address generator to mask one of the following address components: * City * City State * Country * Country Code * State * State Abbreviation * Zip Code * Latitude * Longitude Note that when linked to another address column, a country or country code is always the United States. City, state, and zip code are always real values and match across linked columns. ### Identifying the address component From the address component dropdown list, select the address component that this column contains. #### Supported address components (connectors other than Databricks and Spark SDK) For most data connectors, the available address components are: * Building Number * Cardinal Direction (North, South, East, West) * City * City Prefix (Examples: North, South, East, West, Port, New) * City Suffix (Examples: land, ville, furt, town) * City with State (Example: Spokane, Washington) * City with State Abbr (Example: Houston, TX) * Country (Examples: Spain, Canada) * Country Code (Uses the 2-character country code. Examples: ES, CA) * County * Direction (Examples: North, Northeast, Southwest, East) * Full Address * Latitude (Examples: 33.51, 41.32) * Longitude (Examples: -84.05, -74.21) * Ordinal Direction (Examples: Northeast, Southwest) * Secondary Address (Examples: Apt 123, Suite 530) * State (Examples: Alabama, Wisconsin) * State Abbr (Examples: AL, WI) * Street Address (Example: 123 Main Street) * Street Name (Examples: Broad, Elm) * Street Suffix (Examples: Way, Hill, Drive) * US Address * US Address with Country * Zip Code (Example: 12345) Note that street values are always generated and do not reflect a real address. To generate addresses with real streets, use the [Valid Address](/app/generation/generators/generator-reference/valid-address.md) generator. #### Supported address components (Databricks and Spark SDK) Databricks and Spark SDK workspaces only support the following address components: * Building Number * City * Country * Country Code * Full Address * Latitude * Longitude * State * State Abbr * Street Address * Street Name * Street Suffix * US Address * US Address with Country * Zip Code ### Enabling and disabling consistency Toggle the **Consistency** setting to indicate whether to make the column consistent. By default, the consistency is disabled. ### Setting the type of consistency If consistency is enabled, then by default, the generator is self-consistent. To make the generator consistent with another column, from the **Consistent to** dropdown list, select the column. When the Address generator is consistent with itself, then the same value in the source database is always mapped to the same destination value. For example, for a column that contains a state name, Alabama is always mapped to Illinois. When the Address generator is consistent with another column, then the same value in the other column always results in the same destination value for the address column. For example, if the address column is consistent with a name column, then every instance of John Smith in the name column in the source database has the same address value in the destination database. ### Setting case sensitivity for consistency When consistency is enabled, use the **Case-sensitive** toggle to indicate whether the consistency is case-sensitive. By default, consistency is case-sensitive. For example, the values `Anytown` and `ANYTOWN` are considered different values. `Anytown` might always be replaced with `Chicago`, and `ANYTOWN` might be replaced with `Atlanta`. To make the consistency case-insensitive, toggle **Case-sensitive** to the off position. When the consistency is case-insensitive, `Anytown` and `ANYTOWN` are considered the same value and have the same replacement. ### Enabling Structural data encryption If [Structural data encryption](/app/generation/generators-assign-config/generators-data-encryption-config.md) is enabled, then to use it for this column, in the advanced options section, toggle **Use data encryption process** to the on position. --- # 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. 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