Deduplication And Compression

Data keeps growing as its use in society, the business sector, and the world increases. With more data being processed, there is a rising need for higher storage capacity as backing up extensive data poses challenges like high cost and inefficient bandwidth and storage use. What if we could lessen the storage burden by preserving data and information more efficiently and cost-effectively?

Data reduction techniques present a solution to storage problems by providing a way to reduce data without loss of crucial information or integrity. With these techniques, people, businesses, and organizations can back up data in a compact form and lessen bandwidth consumption while ensuring they can retrieve the stored information without loss.

This article explores the main methods of backup size reduction, deduplication, and decompression. It also discusses their pros, cons, and the best technique for reducing backup size.

Are Data Reduction Techniques Necessary?

Data reduction techniques are necessary for reducing backup size because they provide valuable solutions to the problems that large data files present. Such issues include the need for a more efficient and effective way to store data to reduce cost, storage space, and bandwidth without affecting data integrity or causing data loss.

With data reduction methods, like deduplication and compression, businesses, organizations, and individuals can store data in compact sizes, optimizing storage and bandwidth usage. No negative compromises are made when condensing backup files as all the data, both redundant and non-redundant, can easily be retrieved when needed. Also, bigger data sizes make it more challenging to keep track of useful information. However, by condensing backup sizes, you also reduce the time spent sorting and reading data, leading to higher productivity.

Let’s take a closer look at the two data reduction methods, how they work and are they necessary and worth using for backup size reduction.

What is Deduplication?

Data deduplication entails removing identical data to reduce the storage required to store a large chunk of data. It involves identifying and eliminating redundancy by removing repetitive blocks and saving only one instance of these blocks. However, it references the duplicate blocks so they can be successfully recovered when needed.

Let’s assume you want to back up a folder. During the deduplication process, the algorithm scans the data blocks for identical data. Once the algorithm finds similar data chunks, it only stores one instance of comparable data, so there will only be unique data blocks. Each chunk will then be indexed for identification so users can reconstruct the data when needed.

Deduplication Methods

There are different methods for deduplicating data blocks. However, we will only discuss the three main techniques:

  • Inline Deduplication

The inline method involves deduplicating data in real-time. While backing up the data, the algorithm scans through it for redundancy. It removes repetitive data and only sends non-redundant blocks to the backup destination.

  • Post-process Deduplication

Post-process deduplication doesn’t filter redundancy in real time. Instead, it deduplicates data when it has been backed up. After backup, the blocks will then be deduplicated to eliminate identical blocks. Although it achieves the same result as inline deduplication, it consumes more space and bandwidth. So, you must have enough storage space to accommodate all the data and a higher bandwidth.

  • Global Deduplication

The global deduplication combines the inline and post-process methods. If you use one deduplication method, there may still be some identical storage blocks, so this process enables you to run a double-check to ensure no duplicate block evades elimination.

Advantages of Deduplication

  • Data Retention: Deduplication ensures that there is no loss of data during the reduction process. Although it eliminates redundancy, there is no data loss because you can retrieve the original data form.
  • Lower Bandwidth consumption: It helps to reduce the bandwidth needed when backing up or transferring data.
  • Cost-effective Solution: Deduplication helps to save costs by reducing the size of blocks to be stored.
  • High-level Performance: The size of the data transferred reduces during deduplication. Hence, it makes the process faster and enhances the processing time, saving cost and time.
  • Disadvantages of Deduplication
  • Potential Loss of Data Integrity: Data chunks can get corrupted when there is a mix-up. Also, if the reference block is lost, all blocks under it will get lost.
  • Complexity: Deduplication requires extra hardware resources, which makes it hard to use and more expensive to implement.
  • Lastly, you cannot use this method when there is no redundancy, so it’s not always an effective way to reduce storage requirements.

What is Compression?

Compression reduces the size of data files by encoding or modifying them to reduce the original file size, making them smaller and more compact. Unlike deduplication, which works at the block level, compression works at the file level. To compress a file, the algorithm identifies duplicated or unnecessary information by figuring out the parts it can eliminate without compromising the quality of the original information. The redundant data will then be removed while the rest is rearranged.

Compression Methods

There are two ways to compress files:

  • Lossy Compression

The lossy compression reduces file sizes by eliminating unimportant parts of multimedia files. For example, an audio recording can shrink into an MP3 format, which stores large audio files within a few MB. Inaudible sound frequencies and other non-crucial elements will be removed during conversion. So, while there’s a loss of audio fidelity, it still offers an acceptable audio quality.

Compression also works for RAW photographs, which are compressed into jpeg format. There is a loss of data, but this loss is not noticeable. Thus, it doesn’t negatively affect the final image presented after compression.

  • Lossless Compression

The lossless compression method also eliminates information from a file. It compresses files by looking for redundancies and then saving them for reference. This way, you can still reconstruct the compressed file to obtain its original format. It works by checking the file and representing repetitive data with a placeholder for recognition. So, all redundant files fall under a single identifier, reducing the file size when backing it up. The lossless compression process is mainly used for data backup because a loss of a bit of data information can affect its integrity. It is also used to create zip files, which the user can retrieve.

Advantages of Compression

  • Less Disk Space: Compression reduces the space needed to store data, providing more disk space for other purposes.
  • Faster File Transfer: Shrinking the file size helps to increase the transfer speed as larger file sizes take longer to send. Compressed files won’t take as much time to back up.
  • Faster to read and write: Compressed files take less time to read and write than the original file, thereby reducing operational time.
  • Preserve Data Integrity: Data integrity can easily be preserved through compressing files into a Zip file. There’s no loss of crucial information.
  • Cost-efficient Storage: Compression reduces the cost of storage by making files more compact.

Disadvantages of Compression

  • Decompressing Takes Time: Decompressing a sizable compressed file can be time-consuming, leading to a slowdown in the overall operation. It’s a trade-off between file size reduction and the time it takes to decompress.
  • It Requires Special Decompressing Programs: You will need special programs to decompress these files, and such programs are not easily accessible by users.
  • Requires More Memory: The process often requires additional memory usage when compressing data. In cases of limited memory, encountering an error code is expected.

Which Data Reduction Technique is Best for Reducing Backup Size?

Deduplication is the most commonly used method for backup size reduction, especially for cloud storage backups. It helps to reduce data size to manage storage space and minimize storage costs. Deduplication also ensures that there are no losses during the reduction process. It only stores redundant blocks under a reference block to decrease the backup size. Hence, you will get your original data whenever you want to retrieve it.

Compression may also be used for backup reduction. However, the lossy compression method is unsuitable for data backup because it causes permanent loss of some data elements. When used for backups, it can lead to loss of crucial information. Hence, it’s only suitable for condensing multimedia files like audio, videos, and images. On the other hand, you can use the lossless compression method to condense backup data since this technique ensures recovery of the original data after compression. You can use both deduplication and lossless compression techniques to reduce backup sizes, but deduplication is faster since you don’t have to decompress it when needed.

However, for the best results, you can employ both methods. First, deduplicate backup data to eliminate redundancy, then compress it to reduce the file size further. Doing so will help you save more storage space and reduce the cost of backup.

Conclusion

The two data reduction techniques, deduplication, and compression, are valuable tools for reducing backup size in today’s big data world. There is an explosion of information and data, and backing up such data is cost-intensive and increases storage footprint and bandwidth waste. Thus, it’s necessary to find effective means to reduce backup size. The deduplication method is more commonly used for decreasing backup sizes. However, you can also use the lossless compression method to eliminate repetitive elements from a file without compromising the data integrity.

The best practice is to combine both techniques to ensure optimum storage management. Deduplication eliminates redundancies, while compression further reduces the file size, resulting in a compact-sized backup file.

text written by:

Grzegorz Pytel, Presales Engineer at Storware