Data synchronization aims to maintain consistent and up-to-date copies of data across different systems, ensuring that all users have access to the same information.

Mirroring involves creating an exact copy of data on multiple storage devices or servers, ensuring that if one copy becomes unavailable, the other remains accessible.

Data replication aims to create multiple copies of data in different locations, increasing the likelihood that data remains accessible even if one copy fails.

Local replication creates multiple copies of data within a single data center, typically on different servers, to improve data availability and performance.

Synchronous replication guarantees that all copies of data are updated simultaneously, ensuring immediate data consistency across all systems.

Asynchronous replication permits a slight delay in updating data copies, allowing for higher performance and scalability, but potentially leading to temporary data inconsistencies.

The primary challenge in data synchronization lies in maintaining data consistency across multiple systems, ensuring that all copies of data are up-to-date and accurate.

Incremental replication involves transferring only the changes made to data since the last synchronization, reducing the amount of data that needs to be transferred.

Full replication guarantees that all copies of data are identical, ensuring immediate data consistency across all systems.

Synchronous replication is often preferred in distributed database systems to ensure immediate data consistency, guaranteeing that all database transactions are committed successfully on all replicas.

Synchronous replication can introduce performance bottlenecks due to the need to wait for all replicas to acknowledge data updates before committing the transaction.

Master-slave replication involves maintaining a single master copy of data and multiple read-only replicas, allowing for efficient read operations while ensuring data consistency.

Peer-to-peer replication offers high data availability by maintaining multiple copies of data on different nodes, ensuring that data remains accessible even if some nodes fail.

Active-passive replication is often used in cloud computing environments, where one node serves as the active server handling read and write operations, while the other nodes act as passive replicas for failover.

The primary challenge associated with data replication is managing data storage costs, as maintaining multiple copies of data can significantly increase storage requirements.