What is the impact of enabling data deduplication on performance?

• A. It always slows performance significantly.
• B. It eliminates the need for backups.
• C. Dedup can add CPU overhead but reduces storage; impact depends on workload and data patterns.
• D. It increases network bandwidth.

Answer: (C)

Data deduplication changes performance by trading compute for storage efficiency. When dedup is enabled, the system must compute fingerprints for data blocks, search for duplicates, and manage metadata to map duplicates to a single copy. This adds CPU overhead and can introduce write latency, especially on workloads with lots of small writes or tight latency requirements. However, because duplicates are eliminated, less data is written to disk and read from storage, which can reduce I/O and improve throughput for data with high redundancy. The net effect isn’t fixed—it depends on the workload and how repetitive the data is. For highly redundant data, the storage and I/O savings can outweigh the extra CPU work, leading to comparable or better performance; for workloads with little duplication, the CPU overhead may be more noticeable. Deduplication does not replace backups, and it isn’t a method to increase network bandwidth.