Answer: DBMS performance is improved through measures like indexing, query optimization, normalization, caching, and so on.
Optimizing DBMS performance enhances efficiency and reliability.
- Query Optimization: Query Optimization involves enhancing SQL queries for efficiency by analyzing execution plans and utilizing appropriate indexing strategies.
- Indexing: Indexing entails creating indexes on frequently queried columns and accelerating data retrieval by enabling quick lookup.
- Normalization: Normalization organizes data into normalized tables, reducing redundancy and enhancing storage efficiency.
- Denormalization (Selective) : Selective Denormalization strategically introduces redundancy to minimize joins and enhance query performance in specific scenarios.
- Partitioning: Partitioning divides large tables into smaller partitions based on criteria such as range or hash, improving query performance.
- Caching: Caching mechanisms store frequently accessed data in memory, enabling faster retrieval and reducing database load.
- Hardware Upgrade: Hardware Upgrades involve enhancing system resources like RAM, CPU, and storage to efficiently handle larger workloads.
- Query Tuning: Query Tuning fine-tunes queries by analyzing execution plans, identifying bottlenecks, and optimizing SQL code for better performance.
- Storage Optimization: Storage Optimization utilizes efficient mechanisms like compression and data deduplication to minimize disk usage and enhance efficiency.
- Concurrency Control: Concurrency Control mechanisms ensure efficient locking and handling of multiple concurrent transactions, enhancing overall database performance.
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