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The performance and scalability of databases are crucial for enhancing user experience. Important factors affecting database performance include item size, item type, dataset size, and throughput requirements. Seven effective techniques for optimizing database performance include indexing, materialized views, denormalization, vertical scaling, caching, replication, and sharding. Each technique offers unique benefits and trade-offs. Indexing improves query speed but uses additional disk space, while materialized views reduce query time but require extra storage. Denormalization enhances read performance at the cost of data redundancy. Vertical scaling boosts performance but has hardware limits. Caching decreases database load and read time but may involve data staleness. Replication enhances read performance and availability yet introduces replication lag. Finally, sharding enables horizontal scaling and cost reductions but adds complexity in data management.

7 Techniques for Database Performance & Scaling