Visual Explain in DB2 provides a graphical representation of the query plan. It helps users understand how DB2 executes their queries, showing details such as access methods, join types, and sorting operations. This visualization aids in optimizing query performance by identifying potential bottlenecks or inefficiencies in the execution plan. 

The key difference lies in how they handle unmatched rows. INNER JOIN returns only the rows that have matching values in both tables, whereas OUTER JOIN returns all rows from both tables, with unmatched rows filled with NULL values. 

DB2 Connect facilitates integration between distributed systems and mainframe systems by providing enhanced security features such as encryption and authentication. These features ensure secure communication between distributed systems and mainframes, safeguarding sensitive data during transit. 

A comprehensive disaster recovery plan for a DB2 environment typically includes regular data backups to ensure data integrity and availability. Log shipping mechanisms are employed to replicate transaction logs to a standby server for point-in-time recovery. Standby servers serve as failover targets in case the primary server becomes unavailable. These components work together to minimize downtime and data loss in the event of a disaster. 

The PRIMARY KEY constraint in DB2 ensures entity integrity by uniquely identifying each record in a table. This means that each row in the table is uniquely identifiable, preventing duplicate entries and ensuring the integrity of the data model. 

Denormalization increases data redundancy in a database. When denormalizing, redundant data is intentionally introduced to improve query performance by reducing joins. However, this can lead to potential issues such as data inconsistency and increased storage requirements. 

Common thresholds monitored by the Health Monitor may include Memory Usage, as excessive memory consumption can significantly impact database performance and overall system stability. 

The Health Monitor plays a pivotal role in bolstering database security and compliance efforts. By monitoring access patterns and auditing user activities, it helps identify potential security vulnerabilities and compliance gaps, allowing administrators to take proactive measures to address them. This contributes significantly to maintaining data integrity and adherence to regulatory standards. 

In DB2, a simple view is a virtual table whose contents are defined by a query and are not stored physically in the database. On the other hand, a materialized view is a physical copy of the result set of a query that is stored in the database. Materialized views can improve query performance by precomputing and storing the results, but they require more storage space and may not always reflect the latest data changes. 

IBM Data Studio facilitates performance tuning of DB2 databases through various features such as automated index optimization, query plan analysis tools, database workload simulation, and integrated database monitoring. These tools enable database administrators and developers to identify performance bottlenecks, optimize SQL queries, and enhance overall database performance. For example, the query plan analysis tools help in understanding how queries are executed, allowing for optimization of inefficient queries. Additionally, the integrated database monitoring feature provides real-time insights into database performance metrics, aiding in proactive performance tuning efforts. 

Visual Explain aids in providing insights into the physical characteristics of query execution plans, such as access methods, join methods, and sorting operations, which are crucial for understanding query performance. 

A full database backup in DB2 refers to a snapshot of the entire database at a specific point in time. This backup includes all the data, schema objects, and configurations necessary to restore the database to the state it was in when the backup was taken. It's essential for disaster recovery and restoring databases in case of data loss or corruption.