Add support for monitoring SQL Server databases by using its change data capture feature, which records inserts, updates, and deletes in specific tables that mirror the column structure of the tracked source tables.

This involves creating a Kafka Connect source connector for SQL Server that creates source tasks as needed. Each source task remotely connects to a SQL Server database (with a JDBC driver?) and uses change data capture query functions to read the individual change events from the change tables. When run as part of Kafka Connect, the resulting data change events will be recorded in Kafka logs, and if anything fails Kafka Connect will figure out what was last successfully written and restart a source task to start reading from the next point.

The connector should ideally provide the same behavior, functionality, and options as the MySQL connector (and any other existing relational connectors). Where possible, this connector should also use the same configuration fields as other connectors.