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Write policies are only available to select accounts. Contact your Immuta representative to enable this feature.
Immuta offers two types of subscription policies to manage read and write access in a single system:
Read access policies manage who can read data.
Write access policies manage who can modify data.
Both of these access types can be enforced at any of the restriction levels outlined in the Subscription policies reference guide.
The table below illustrates the access types supported by each integration.
| Integration | Read access policies | Write access policies |
|---|---|---|
To create a read or write access policy, see the Author a subscription policy guide.
Once a read or write access policy is enforced on an Immuta data source, it translates to the relevant privileges on the table, view, or object in the remote platform. The sections below detail how these access types are enforced for each integration.
The Snowflake integration supports read and write access subscription policies. However, when applying read and write access policies to Snowflake data sources, the privileges granted by Immuta vary depending on the object type. For example, users can register Snowflake views as Immuta data sources and apply read and write policies to them, but when a write policy is applied to a view only the SELECT privilege will take effect in Snowflake, as views are read-only objects.
Users can register any object stored in Snowflake’s information_schema.tables view as an Immuta data source. The table below outlines the Snowflake privileges Immuta issues when read and write policies are applied to various object types in Snowflake. Beyond the privileges listed, Immuta always grants the USAGE privilege on the parent schema and database for any object that access is granted to for a particular user.
The Databricks Unity Catalog integration supports read and write access subscription policies. When users create a subscription policy in Immuta, Immuta uses the Unity Catalog API to issue GRANTS or REVOKES against the catalog, schema, or table in Databricks for every user affected by that subscription policy.
Users can register any object stored in Databricks Unity Catalog’s information_schema.tables view as an Immuta data source. However, when applying read and write access policies to these data sources, the privileges granted by Immuta vary depending on the object type. For example, users can register foreign tables as Immuta data sources and apply read and write policies to them, but only a read policy will take effect in Databricks and allow users to SELECT those tables. If a write policy is applied, Immuta will not issue SELECT or MODIFY privileges in Databricks.
The table below outlines the Databricks privileges Immuta issues when read and write policies are applied to various object types in Databricks Unity Catalog. Beyond the privileges listed, Immuta always grants the USAGE privilege on the parent schema and catalog for any object that access is granted to for a particular user.
The Databricks Spark integration supports read access subscription policies. When a read access policy is applied to a data source, Immuta modifies the logical plan that Spark builds when a user queries data to enforce policies that apply that user. If the user is subscribed to the data source, the user is granted SELECT on the object in Databricks. If the user does not have read access to the object, they are denied access.
The Starburst (Trino) integration supports read and write access subscription policies. In the Starburst (Trino) integration's default configuration, the following access values grant read and write access to Starburst (Trino) data when a user is granted access through a subscription policy:
READ: When a user is granted read access to a data source, they can SELECT on tables or views and SHOW on tables, views, or columns in Starburst (Trino). This setting in enabled by default when you configure the Starburst (Trino) integration.
WRITE: In its default setting, the Starburst (Trino) integration's write access value controls the authorization of SQL operations that perform data modification (such as INSERT, UPDATE, DELETE, MERGE, and TRUNCATE). When users are granted write access to a data source through a subscription policy, they can INSERT, UPDATE, DELETE, MERGE, and TRUNCATE on tables and REFRESH on materialized views. This setting is enabled by default when you configure the Starburst (Trino) integration.
Administrators can customize write access configuration to grant additional Starburst (Trino) table modification privileges. See the Custom configuration section below for an overview and example configurations.
Because Starburst (Trino) can govern certain table modification operations (like ALTER) separately from data modification operations (like INSERT), Immuta allows users to specify what modification operations are permitted on data in Starburst (Trino). Administrators can allow table modification operations (such as ALTER and DROP tables) to be authorized as write operations through advanced configuration in the Immuta web service or Starburst (Trino) cluster with the following access values:
OWN: When mapped via advanced configuration to Immuta write policies, users who are granted write access to Starburst (Trino) data can ALTER and DROP tables and SET comments and properties on a data source.
CREATE: When this privilege is granted on Starburst (Trino) data, an Immuta user can create catalogs, schemas, tables, or views on a Starburst (Trino) cluster. CREATE is a Starburst (Trino) privilege that is not controlled by Immuta policies, and this property can only be set in the access-control.properties file on the Starburst (Trino) cluster.
Administrators can customize table and data modification settings in one or both of the following places; however, the access-control.properties overrides the settings configured in the Immuta web service:
Immuta web service: Configuring write policies in the Immuta web service allows all Starburst (Trino) clusters targeting that Immuta tenant to receive the same write policy configuration for Immuta data sources. This configuration only affects tables or views registered as Immuta data sources. Use the option below to control how unregistered data is affected.
Starburst (Trino) cluster: Configuring write policies using the access-control.properties file on a Starburst (Trino) cluster allows access to be broadly customized for Immuta users on that cluster. This configuration file takes precedence over write policies passed from the Immuta web service. Use this option if all Immuta users should have the same level of access to data regardless of the configuration in the Immuta web service.
Immuta web service access grants mapping
Customizing read and write access in the Immuta web service affects operations on all Starburst (Trino) data registered as Immuta data sources in that Immuta tenant. This configuration method should be used when all Starburst (Trino) data source operations should be affected identically across Starburst (Trino) clusters connected to the Immuta web service. Example configurations are provided below. Contact your Immuta representative to customize the mapping of read or write access policies for your Immuta tenant.
Default configuration
The default setting shown below maps WRITE to READ and WRITE permissions and maps READ to READ. Both the READ and WRITE permission should always include READ.
In this example, if a user is granted write access to a data source through a subscription policy, that user can perform data modification operations (INSERT, UPDATE, MERGE, etc.) on the data.
Custom configuration
The following configuration example maps WRITE to READ, WRITE, and OWN permissions and maps READ to READ. Both READ and WRITE permissions should always include READ.
In this example, if a user gets write access to a data source through a subscription policy, that user can perform both data (INSERT, UPDATE, MERGE, etc.) and table (ALTER, DROP, etc.) modification operations on the data.
Starburst (Trino) cluster access grants mapping
The Starburst (Trino) integration can also be configured to allow read and write policies to apply to any data source (registered or unregistered in Immuta) on a specific Starburst (Trino) cluster.
The default setting shown below maps WRITE to READ and WRITE permissions and maps READ to READ. Both the READ and WRITE permission should always include READ.
In this example, if a user is granted write access to a data source through a subscription policy, that user can perform data modification operations (INSERT, UPDATE, MERGE, etc.) on the data.
The following configuration example maps WRITE to READ, WRITE, and OWN permissions and maps READ to READ. Both READ and WRITE permissions should always include READ.
In this example, if a user gets write access to a data source through a subscription policy, that user can perform both data (INSERT, UPDATE, MERGE, etc.) and table (ALTER, DROP, etc.) modification operations on the data.
Two properties customize the behavior of read or write access for all Immuta users on that Starburst cluster:
immuta.allowed.immuta.datasource.operations: This property governs objects (catalogs, schemas, tables, etc.) that are registered as data sources in Immuta. For these permissions to apply, the user must be subscribed in Immuta and not be an administrator (who gets all permissions).
immuta.allowed.non.immuta.datasource.operations: This property governs objects (catalogs, schemas, tables, etc.) that are not registered as data sources in Immuta. This is the only property that allows the CREATE permission, since CREATE is enforced on new objects that do not exist in Starburst or Immuta yet (such as a new table being created with CREATE TABLE).
The default configuration and an example of a custom configuration are provided below. See the Customize read and write access policies in Starburst page for guidance on configuring these properties in your Starburst cluster.
Default configuration
By default, Immuta allows READ and WRITE operations to be authorized on data registered in Immuta, while all operations are permitted for data sources that are not registered in Immuta.
Custom configuration
In the example below, the configuration allows READ, WRITE, and OWN operations to be authorized on data sources registered in Immuta and all operations are permitted on data that is not registered in Immuta. If a user gets write access to data registered in Immuta through a subscription policy, that user can perform both data (INSERT, UPDATE, MERGE, etc.) and table (ALTER, DROP, etc.) modification operations on the data.
The Redshift integration supports read access subscription policies. Immuta grants the SELECT Redshift privilege to the PUBLIC role when the integration is configured, which allows all users who meet the conditions of a subscription policy to access the Immuta-managed view. When a data source is created, Immuta creates a corresponding dynamic view of the table with a join to a secure view that contains all Immuta users, their entitlements, their projects, and a list of the tables they have access to. When a read policy is created or updated (or when a user's entitlements change, they switch projects, or when their data source access is approved or revoked), Immuta updates the secure view to grant or revoke users' access to the data source. If a user is granted access to the data source, they can access the view. If a user does not have read access to the view, zero rows are returned when they attempt to query the view.
The Azure Synapse Analytics integration supports read access subscription policies. Immuta grants the SELECT privilege to the PUBLIC role when the integration is configured, which allows all users who meet the conditions of a subscription policy to access the Immuta-managed view. When a read policy is created or removed (or when a user's entitlements change, they switch projects, or when their data source access is approved or revoked), Immuta updates the view that contains the users' entitlements, projects, and a list of tables they have access to grant or revoke their access to the dynamic view. Users' read access is enforced through an access check function in each individual view. If a user is granted access to the data source, they can access the view. If a user does not have read access to the view, they receive an Access denied: you are not subscribed to the data source error when they attempt to query the view.
The Google BigQuery integration supports read access subscription policies. In this integration, Immuta creates views that contain all policy logic. Each view has a 1-to-1 relationship with the original table, and read access controls are applied in the view. After data sources are registered, Immuta uses the custom user and role, created before the integration is enabled, to push the Immuta data sources as views into a mirrored dataset of the original table. Immuta manages grants on the created view to ensure only users subscribed to the Immuta data source will see the data.
The Amazon S3 integration supports read and write access subscription policies. Users can apply read and write access policies to data in S3 to restrict what prefixes, buckets, or objects users can access or modify. To enforce access controls on this data, Immuta creates S3 grants that are administered by S3 Access Grants, an AWS feature that defines access permissions to data in S3. To query a data source they are subscribed to, users request temporary credentials from their Access Grants instance. These just-in-time access credentials provide access to a prefix, bucket, or object with a permission level of READ or READWRITE in S3. When a user or application requests temporary credentials to access S3 data, the S3 Access Grants instance evaluates the request against the grants Immuta has created for that user. If a matching grant exists, S3 Access Grants assumes the IAM role associated with the location of the matching grant and scopes the permissions of the IAM session to the S3 prefix, bucket, or object specified by the grant and vends these temporary credentials to the requester. If the grant does not exist for the user, they receive an Access denied error.
READ and READWRITE access levelsImmuta read policies translate to the READ access level in S3 Access Grants and Immuta write policies translate to the READWRITE access level. The table below outlines the Amazon S3 actions granted on an S3 data source when users meet the restrictions specified in an Immuta read or write access subscription policy that is applied to the data source. See the AWS documentation for more details about grants, access levels, and actions.
With the exception of the Starburst integration, users can only modify existing data when they are granted write access to data; they cannot create new tables or delete tables.
Write actions are not currently captured in audit logs.
| Snowflake object (information_schema.tables.table_type) | Read policy applied | Write policy applied |
|---|---|---|
| Databricks Unity Catalog object (information_schema.tables.table_type) | Read policy applied | Write policy applied |
|---|---|---|
| Immuta policy | S3 Access Grants access level | Amazon S3 action |
|---|---|---|
Read
READ
GetObject
GetObjectVersion
GetObjectAcl
GetObjectVersionAcl
ListMultipartUploadParts
ListObjects
ListObjectsVersions
ListBucketMultipartUploads
KmsDecrypt
Write
READWRITE
GetObject
GetObjectVersion
GetObjectAcl
GetObjectVersionAcl
ListMultipartUploadParts
ListObjects
ListObjectsVersions
ListBucketMultipartUploads
KmsDecrypt
PutObject
PutObjectAcl
PutObjectVersionAcl
DeleteObject
DeleteObjectVersion
AbortMultipartUpload
KmsGenerateDataKey
Table (BASE TABLE)
SELECT
SELECT, INSERT, UPDATE, DELETE, TRUNCATE
View (VIEW)
SELECT
Materialized view (MATERIALIZED VIEW)
SELECT
External table (EXTERNAL TABLE)
SELECT
Event table (EVENT TABLE)
SELECT
Iceberg table (IS_ICEBERG=YES)
SELECT
Dynamic table (IS_DYNAMIC=YES)
SELECT
Data object from an incoming Data Share
Table (MANAGED)
SELECT
SELECT, MODIFY
View (VIEW)
SELECT
Materialized view (MATERIALIZED_VIEW)
SELECT
Streaming table (STREAMING_TABLE)
SELECT
External table (EXTERNAL)
SELECT
Foreign table (FOREIGN)
SELECT
Data object from incoming Delta Share
There are several different advanced functions that are available for building subscription policies. Some of these functions, listed below, are narrowly focused on orchestrated RBAC use cases. Orchestrated RBAC is when an organization has many roles that represent access, and rather than switching to using the ABAC model provided by Immuta, they use these special functions to orchestrate existing roles using Immuta.
Specifically, the functions to enable orchestrated-RBAC are:
@hostname
@database
@schema
@table
@hasTagAsAttribute('Attribute Name', 'dataSource' or 'column')
@hasTagAsGroup('dataSource' or 'column')
Policy:
@hasAttribute('SpecialAccess', '@hostname.@database.*')
User:
has the attribute
SpecialAccesswith the valueus-east-1-snowflake.default.*
The user would be subscribed to all the data sources in the default database. Note this has nothing to do with tags, it is based purely on the physical name of the host, database, schema, and table in the native data platform. Also note that the user attribute contains an asterisk * to denote everything under the default database hierarchy. Asterisks are supported only for the infrastructure special functions:
@hostname
@database
@schema
@table
This is because, since it's an infrastructure view, Immuta can assume a 4-level hierarchy (hostname.database.schema.table) and an asterisk can be placed between any two objects in that 4-level hierarchy to represent any object, such as us-east-1-snowflake.*.hr. That would give the user access to any schema named hr in host us-east-1-snowflake no matter the database.
However, that is not possible when using the tag-based special functions:
@hasTagAsAttribute('Attribute Name', 'dataSource' or 'column')
@hasTagAsGroup('dataSource' or 'column')
This is because Immuta cannot rely on a 4-level hierarchy always being the case. For example, *.Age could mean many things in a tag hierarchy. However it does support using parent attributes to apply to child attributes as described in Example 2.
Lastly, the asterisk represents any object, but cannot be used for a concatenated wildcard like so: snowfl*.tpc.*.*
Policy:
@hasTagAsAttribute('PersonalData', 'dataSource')
User:
has the attribute key
PersonalDatawith the values
Discovered.Person Name
Discovered.Entity
Data source 1:
tagged:
Discovered.Country
Discovered.Passport
Discovered.Person Name
Data source 2:
tagged:
Discovered.State
Discovered.Postal Code
Discovered.Entity.Social Security Number
Data source 3:
tagged:
Discovered.State
Discovered.Passport
The user would be subscribed to data source 1 and 2, but the user would not be subscribed to data source 3. This is because access moves from left-to-right in the hierarchy based on what the user possesses (the wildcard asterisk is implied).
So if a user had a more specific attribute key PersonalData with the values Discovered.Entity.Social Security Number, they would only get access to hypothetical data source 2, because their attribute is further left or matches (in this case matches) Discovered.Entity.Social Security Number.
The below table provides more examples:
It is also possible to build subscription policies separately that use these special functions and have them merge appropriately on data sources.
This could be helpful for use cases with a policy like the following:
If user has the attribute “Allowed_Domain.Domain A” they get access to generic data that is part of domain A.
If user has the attribute “Badge_Allowed.Badge X” they should gain access to both “generic data + any additional data (only in domain A because they only have “Data Domain A General Access”) that has been tagged as “Badge X”.
In this case it can be two separate subscription policies, such as
Policy 1: @hasTagAsAttribute(Allowed_Domain, ‘datasource’) this would limit to the domains where they are allowed to see generic data.
Policy 2: @hasTagAsAttribute(Badge_Allowed, ‘datasource’) this would limit to the badges they are allowed to see.
Then, when the data sources are tagged with table tags that represent access, if the table only has the domain tag, only policy 1 will apply; however, if it has a domain tag and a badge tag, both policies will be applied and merged successfully by Immuta.
While this approach is extremely powerful, in many cases, it will continue to leave you dealing with policy complexity associated with RBAC. Read the Automate data access control decisions use case for more details, specifically The two paths guide.
Write access is controlled through workspaces and scratch paths
View-based integrations are read-only
View-based integrations are read-only
View-based integrations are read-only
| User Attributes | Data Source Tags | Subscribed? | Notes |
|---|---|---|---|
'PersonalData': [Discovered.Person Name, 'Discovered.Entity']
['Discovered.Identifier Indirect', Discovered.Person Name]
Yes
Exact match on Discovered.Person Name
'PersonalData': ['Discovered.Entity']
['Discovered.PHI', 'Discovered.Entity.Age']
Yes
User attribute 'Discovered.Entity' is a hierarchical parent of data source tag 'Discovered.Entity.Age'
'Access': [Discovered.Person Name, 'Discovered.Entity']
['Discovered.Identifier Indirect', Discovered.Person Name]
No
The policy is written to only match values under the 'PersonalData' attribute key. Not 'Access'.
'PersonalData': ['Discovered']
['Discovered.Entity.Age']
Yes
User attribute 'Discovered' is a hierarchical parent of data source tag 'Discovered.Entity.Age'
'PersonalData': ['Discovered.Entity.Social Security Number']
['Discovered.Entity']
No
Hierarchical matching only happens in one direction (user attribute contains data source tag). In this case, the user attribute is considered hierarchical child of the data source tags.