Data Compression vs Deduplication (PDF)
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Summary
This document discusses the trade-offs between data compression and data deduplication, explaining the principles behind each method and how they might affect storage and transmission in different contexts.
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❗ 213 Data Compression vs Data * * * * Deduplication (Trade-offs) *...
❗ 213 Data Compression vs Data * * * * Deduplication (Trade-offs) * * ** Data Compression and Data Deduplication are two techniques used to optimize data * *** ** * *** * ** storage, but they function in different ways and are suited for different scenarios. *** Data Compression * * ** Definition: Data Compression involves encoding information using fewer bits than the ** ** * *** * * original representation. It reduces the size of data by removing redundancies *** ** ~~ ~~* and is often used to save storage space or decrease transmission times. *** *** *** ~~ ~~ *** ** Types: ** ** Lossless Compression: Reduces file size without losing any data (e.g., ZIP files). You ** ** ** can restore data to its original state. ** Lossy Compression: Reduces file size by permanently eliminating certain information, ** * * especially in media files (e.g., JPEG images, MP3 audio). *** *** ** ** ** ** ** Example: When you compress a text document using a ZIP file format, ** *** *** it uses algorithms to find and eliminate redundancies, reducing the file size. ~~ ~~ * * The original document can be perfectly reconstructed when the ZIP file is * ** ** ** decompressed. ** * ** Pros: ** ** Efficient Storage: Saves storage space. ** ** Faster Transmission: Reduces data transmission time over networks. ** * ~~ ~~ * ** Cons: ** ** Processing Overhead: Requires computational resources for compressing and ** * * decompressing data. ** Quality Loss in Lossy Compression: Can lead to quality degradation in media files. ** * ~~ ~~ * ❗ Data Deduplication ** Definition: Data Deduplication is a technique for eliminating duplicate copies of repeating ** ** ** ~~ data. It is used in data storage and backup systems to reduce the amount of storage space ~~ * * * * * needed. * ** Process: ** 1. Identify Duplicates: The system identifies and removes redundant data segments, ** ** keeping only one copy of each segment. 2. Reference Links: Subsequent copies are replaced with pointers to the stored segment. ** ** ** Example: In a corporate backup system, ** *** *** many employees might have the same file saved on their computers. * * * Instead of storing each copy, Data Deduplication stores one copy and then references * ** ** * to that copy for all subsequent identical files. * ** Pros: ** ** Significantly Reduces Storage Needs: Particularly effective in environments with lots * * ** * of redundant data, like backup systems. * *** *** ** Optimizes Backup Processes: Makes backups more efficient by reducing the amount of ** data to be backed up. ** Cons: ** *** Limited to Identical Data: Only reduces data that is exactly the same. * * * ** * * ** Resource Intensive: Requires processing power to identify duplicates. ** * * Key Differences * * ** Method of Reduction: ** ** Data Compression reduces file size by eliminating redundancies within a file, ** ~~ ~~ *** *** * whereas Data Deduplication eliminates redundant files or data blocks across a * ** ** ~~ ~~ *** *** *** *** *** *** system. ** Scope: ** ** Data Compression works on a single file or data stream, ** *** *** * * *** *** *** *** while Data Deduplication works across a larger dataset or storage system. ** ** * * ** Restoration: ** * Compressed data can be decompressed to its original form, * * * *** but deduplicated data relies on references to the original data for restoration. *** * * * * Conclusion ** Data Compression is useful for reducing the size of individual files for storage and ** * ** ** transmission efficiency. * In contrast, Data Deduplication is ideal for large-scale storage systems where the ** ** * ** ** same data is stored or backed up multiple times. * * Both techniques can significantly improve storage efficiency, but they are used in * *** *** * different contexts and often complement each other in comprehensive data storage * *** *** and management strategies.