How do partitioning, sharding, and replication concepts differ and relate to each other in distributed systems?

Partitioning, sharding, and replication are different techniques for scaling and increasing fault tolerance in distributed systems:

• Partitioning (Partitioning): dividing data into parts (partitions) based on a certain attribute (e.g., key range or hashing). Each partition is stored separately, allowing parallel processing and reducing load on individual nodes.

• Sharding: a specific case of partitioning where data is distributed across different servers (shards). Each shard contains part of the data and operates as a separate database. It helps horizontally scale the system.

• Replication: creating copies of data on multiple nodes to increase availability and fault tolerance. Usually, there is a master (primary) and slaves (copies) that can serve read requests.

In summary:

• Partitioning and sharding are related to data separation.
• Replication is related to copying data for reliability.

Example: a database with millions of records can be sharded by users (sharding), and each shard can be replicated for fault tolerance.