What are the possible Data transfer methods and why are they used for in general?

Problem:  What are the possible Data transfer methods and what are they used for in general?

Solution: In some situations, companies create High availability, Disaster Recovery for reducing time when there is a fatal error or database server crashed due to fire accident or something like that.

In some scenarios companies try to create a separate data ware house for real time reporting from the OLTP database using data transfer methods.

So, we have a wide variety of things that can be done using SQL server from a data transfer/ high availability stand point. I have created a matrix out of few blogs, Microsoft and some of my research.

This can help you decide when to use which kind of methodology and what is it commonly used for. Also on a side note I have compared all the Pros and cons.

Methods	Pros	Cons	Commonly Used for
Log Shipping	1. Low maintenance	user’s connections need to be kicked out, when new log is applied.	High Availability Solutions/ Disaster Recovery
Database Mirroring	1. Log Files are Continuously Merged	1. needs constant refresh of the Snapshot database for latest data	High Availability Solutions
		2. Database needs to be in Full recovery model
Database Snapshot	1. Quick Back and Restore	1. May Break Log sequence
	2. Changes are captured by pages	2. Enterprise Edition only
Transactional Replication	1. Instant updates to Target	1.When an upgrade has drop statements (Uninstall and install replication)	Best for Reporting
	2. Change Tracking is default	2.Limitations of data transformation
	3. Can filter data sent to target(tables)
	4. Publisher and subscribers are both active
Failover Clustering	SAN(Hardware+OS)	1. No changes allowed at failover location	High Availability Solutions/Disaster Recovery
		2. data on Failover is not available for queries while the Primary server is running
		3. Needs to be Server Level, cannot be at a database level
Backup Restore (Full, Differential, transactional)	1. Simple Method to setup	1. No Control on the Source to filter data
	2. Low maintenance	2. Old approach
SSIS ETL	1.Data Transformations, aggregations, Customizable	1. Needs Change Tracking, building ware house is Time consuming	Best for Reporting
	2. Larger datasets process faster	2. Depending on the Refresh intervals it can affect the server performance
Always on Availability	Backups can be moved to primary database	cost of enterprise license	High Availability Solutions/Disaster Recovery
		SQL 2016 enterprise edition