A rollback plan is crucial in data migration testing as it ensures that in case of any failures or issues during migration, the system can be reverted back to its previous state, minimizing risks and ensuring data integrity.

ACID stands for Atomicity, Consistency, Isolation, and Durability, which are the four properties ensuring the reliability of transactions in a database system.

To prevent conflicts with existing schemas during CI/CD pipeline executions, it's essential to use a database migration tool that supports schema comparison, enabling the tool to identify and resolve any conflicts before applying migration scripts.

Referential integrity constraint ensures that values in one column (or a group of columns) in one table correspond to values in another table's column(s) with a primary key constraint.

Continuous integration involves frequently integrating code changes into a shared repository and running automated tests. This practice ensures that any bugs introduced are identified and fixed early in the development process, reducing the likelihood of them propagating to later stages, including database updates.

The aspect of database testing that emphasizes verifying data consistency and reliability is data validation. Data validation involves checking whether the data stored in the database meets specific criteria, such as accuracy, completeness, and consistency. By performing thorough data validation tests, testers can ensure that the data remains consistent and reliable throughout various operations and interactions with the application.

Access Control Lists (ACLs) are used in database security to specify the access privileges granted to users or groups for specific database objects. An ACL consists of a list of permissions associated with a resource, indicating which users or system processes are granted access and what operations are allowed for those users or processes. By configuring ACLs, database administrators can control who can access and manipulate the data stored in the database, helping to enforce security policies and protect sensitive information.

Load testing assesses the system's performance under expected load levels, including the ability to handle an increasing number of transactions. It helps determine the system's response time and resource utilization under typical usage scenarios.

Large and complex databases introduce data integration challenges in database testing. Testing against such databases requires careful consideration of how different components interact and exchange data, as well as ensuring the accuracy and consistency of data across various systems. Managing these integration challenges is crucial for comprehensive testing and ensuring the reliability of the database system.

Load testing involves assessing the system's performance metrics, such as throughput and response times. These measurements provide insights into how efficiently the system processes requests under different load conditions.