Scaling a database is essential as an application grows to maintain optimal performance. Strategies include: vertical scaling, adding resources to one server; indexing, creating indexes on frequently queried columns; sharding, splitting data across different servers; vertical partitioning, separating columns into smaller tables; caching, storing frequently accessed data in a faster storage layer; replication, creating copies of the database in different regions; materialized views, pre-computing and storing complex query results; and data denormalization, introducing redundancy to optimize reads by combining tables. Each method has trade-offs and can be combined based on application needs.

6m read timeFrom blog.algomaster.io
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Table of contents
1. Vertical Scaling2. Indexing3. Sharding4. Vertical Partitioning5. Caching6. Replication7. Materialized Views8. Data Denormalization
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