Database
Preparing and connecting the IdentityIQ database (Oracle, SQL Server, MySQL).
Create the database and user, run the provided DDL scripts to build the schema, then point IdentityIQ at it via the datasource.
- Prerequisites for Database
- Step-by-step install path
- Common pitfalls and fixes
- Verification after install
The database is the heart of IdentityIQ, it is the identity warehouse holding every object the platform knows about. Preparing it correctly, creating the schema from the vendor-supplied scripts, granting the right privileges, and connecting IdentityIQ to it, is foundational, and its sizing and health dominate performance for the life of the deployment.
Supported databases
IdentityIQ supports Oracle, Microsoft SQL Server and MySQL (check the compatibility matrix for exact versions). Choose based on your organisation's standards and expertise; all are viable when properly sized and tuned.
Step by step
- 1. Create the database and a dedicated service account for IdentityIQ.
- 2. Run the supplied DDL scripts for your database type to build the schema, never hand-craft the schema.
- 3. Grant the required privileges to the service account (the scripts and docs specify what is needed).
- 4. Configure the datasource in IdentityIQ with the connection details and credentials.
- 5. Verify connectivity and confirm the schema version matches the release.
Sizing and indexing
Size the database for your object volume, identities times average links, plus entitlements, roles and, critically, certification and audit history, which grow over time. Ensure the vendor-recommended indexes exist, and add indexes for any extended attributes you filter or search on heavily. An under-indexed, under-sized database is the classic root cause of poor IdentityIQ performance.
Upgrades and schema changes
When you upgrade IdentityIQ, run the provided schema upgrade scripts, do not modify tables by hand. Keeping the schema strictly under the vendor's scripts is what makes upgrades and support tractable.
Verify
Confirm the service account connects, the schema is present at the correct version, and a test aggregation writes and reads data successfully.
Common pitfalls
- Hand-editing the schema instead of using the supplied scripts.
- Under-sizing/under-indexing, the top performance problem.
- Insufficient privileges on the service account.