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**Partitioning** and **sharding** share the same idea, in both cases large data gets split into parts. But the key difference is **where and why those parts are stored**.

### Partitioning

- **Where:** every partition lives **on a single server** (within one database).
- **Goal:** improve performance and manageability *within* a single system.
- **Management:** handled by the DBMS itself (e.g. PostgreSQL can partition tables natively).
- **Typical scenarios:** faster queries, cleaning up old data, optimizing storage for large tables.

Example: an orders table split by month, January, February, March, all stored on one server.

### Sharding

- **Where:** each shard lives **on a separate server** or cluster.
- **Goal:** horizontal scaling of the whole system and load distribution.
- **Management:** requires external logic, request routing, synchronization, replication.
- **Typical scenarios:** large web services, millions of users, terabytes of data.

Example: users with IDs 1-1,000,000 on one server, the rest on another.

**In short:**

- Partitioning = splitting a table *within one server*.
- Sharding = splitting a database *across different servers*.

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