When testing complex joins and subqueries, testers should assess data accuracy and correctness. Accuracy ensures that the data returned by the queries is correct and aligned with the expected results. It involves verifying that the joins and subqueries produce the intended outcomes without errors or discrepancies.

Performance testing is conducted to evaluate the system's performance under various workloads. Stress testing, a subset of performance testing, specifically checks the system's response under extreme conditions, such as high loads or concurrent users. In this scenario, the observed issue suggests a need for performance testing, particularly stress testing, to identify and address the performance degradation under heavy concurrent usage.

Version control systems like Git play a crucial role in database testing within a CI environment by tracking changes made to database scripts and configurations. They ensure that all changes are documented, provide a history of modifications, and facilitate collaboration among team members. By maintaining a centralized repository of database scripts, Git enables seamless integration with CI pipelines, allowing for automated testing and deployment of database changes.

SQL is commonly used for writing automation scripts in database testing. SQL (Structured Query Language) is specifically designed for managing and manipulating relational databases. It allows testers to interact with the database, execute queries, and validate the results, making it a preferred choice for database testing automation.

The TRY...CATCH statement is commonly used in SQL to catch and handle errors. It allows developers to encapsulate the code that might generate errors within a TRY block and specify the actions to be taken in case an error occurs in the corresponding CATCH block. This helps in better error handling and ensures that the application remains stable even in the presence of errors.

The DELETE statement in SQL is used to remove one or more rows from a table in a database. It is a Data Manipulation Language (DML) statement that allows users to remove unwanted data from a table, based on a specified condition if needed.

Extraction is the correct option. In the ETL (Extract, Transform, Load) process, the first step is to extract data from the source systems. This involves identifying the relevant data sources and pulling the required data into the ETL pipeline for further processing.

An Application Layer Gateway (ALG) is a firewall filtering technique that makes decisions based on the application layer protocol. ALGs are responsible for understanding and processing application-specific protocols, making them suitable for filtering at the application layer.

The primary function of an Intrusion Detection System (IDS) is to monitor and detect suspicious activities on a network or system for enhanced security.

Performance testing in databases primarily aims to assess the speed and responsiveness of the database system under various conditions such as heavy loads, concurrent users, or large datasets. Performance testing helps identify bottlenecks and optimize database performance.