Data caching is the most likely cause of poor performance, data inconsistency and integrity issues in an IT application, because it involves storing frequently accessed data in a temporary memory location (cache) to reduce the latency and bandwidth consumption of retrieving data from the original source. However, data caching can also introduce problems such as stale data (when the cache is not updated with changes made to the original source), cache coherence (when multiple caches store copies of the same data and need to be synchronized), and cache corruption (when the cache is damaged or tampered with).
Database clustering is not a likely cause of poor performance, data inconsistency and integrity issues, because it involves distributing data across multiple servers or nodes to improve availability, scalability and load balancing of database operations. Database clustering can also enhance data consistency and integrity by using replication and synchronization mechanisms to ensure that all nodes have the same view of the data.
Reindexing of the database table is not a likely cause of poor performance, data inconsistency and integrity issues, because it involves rebuilding or reorganizing indexes on tables or views to improve query performance and reduce fragmentation of index pages. Reindexing can also improve data consistency and integrity by ensuring that indexes reflect the current state of the data in the tables or views.
Load balancing is not a likely cause of poor performance, data inconsistency and integrity issues, because it involves distributing workloads across multiple servers or resources to optimize resource utilization, throughput and response time of applications. Load balancing can also enhance data consistency and integrity by using algorithms and protocols to route requests to the most appropriate server or resource based on availability, capacity and performance.
References:
Data Caching
Database Clustering
Reindexing Database Tables in SQL Server
[Load Balancing]
