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What Is Data Deduplication?

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Data deduplication in storage is a foundational technology for managing data loads, helping users of all types conserve space and perform backups faster. In this article, we look at data deduplication in storage, why it’s important, how it works, and the different types of deduplication processes.  

What Is Data Deduplication?

Data deduplication is the process of eliminating redundant data copies. It’s a data storage optimisation technique that frees up resources by removing non-unique data segments within data sets.  

Why Is Data Deduplication Important?

With the rise of data-driven operations and the digital workplace, organisations of all kinds are managing and using more data and sending it to and from more endpoints than ever. 

Over time, it’s inevitable that duplicate, non-unique data may accumulate within storage systems as organisations go about their day-to-day operations. This redundant data is compounded further when you factor in the need to maintain some intentional redundancy for disaster recovery, high availability, and data protection purposes. 

Duplicate data eats up storage space that could otherwise be repurposed for dealing with the ever-increasing data volumes modern organisations must contend with. By removing this duplicate data, you can free up space without needing to purchase additional capacity to meet growing data demands. 

In other words, investment in solid data deduplication capability translates directly into storage savings. Data deduplication is a foundational process for helping organisations meet their data challenges in the most efficient, streamlined, and cost-sensitive ways possible.

What Are the Benefits of Data Deduplication?

The most obvious benefit is that a smaller storage footprint is required. This can be a significant savings for large organisations with huge data sets, but the benefits go beyond budgets. With data deduplication, backups can be performed more quickly, with fewer compute and storage resources needed. Users can access data more quickly and with fewer errors that can arise due to duplicates and conflicts.

It’s useful to note that the costs of a bloated data estate are incurred again and again over time whenever the data is accessed or moved. Conversely, the benefits of performing deduplication once will continue to provide benefits into the future. 

Deduplication is a foundational technology for making computing work better, which is why it’s built into many systems and run by default. 

How Does Deduplication Work?

While, at its core, deduplication is about removing non-unique instances of data across your data set, there are some technical nuances that are worth investigating regarding how data deduplication works under the hood.

File-level Deduplication

Data deduplication at the file level involves the elimination of duplicate files. The system ensures a file copy is only stored once, linking other references to that first file.  

A familiar example of file-level deduplication is the storage backup process. Most backup programs will, by default, compare the file metadata of the source and target volumes and only rewrite those files with updated modification history—leaving the other files alone. In addition, users usually have the option of erasing from the storage location any files that are missing from the source. 

In enterprise data environments, a similar process is used when importing or merging files or when optimizing storage. File sets are scanned and compared to an index, with non-unique files stored once and only linked from their original locations.

As a result, the process is quicker because the system is copying fewer files, and storage space is saved through the elimination of deleted files. 

Block-level Deduplication

Deduplication can also be performed at the block level—for example, on a database or file. In this case, the system divides the information into data segments of a fixed size called blocks and saves unique iterations of each segment. A unique number is generated for each piece and stored in an index. When a file is updated, rather than write an entirely new file, only the changed data is saved. As a result, block deduplication is more efficient than file deduplication. 

However, block deduplication takes more processing power and requires a larger index to track the individual pieces. Variable-length deduplication is an alternative method that uses segments of varying sizes, which the deduplication system can use to achieve better data reduction ratios than with fixed-length blocks. 

Inline vs. Post-processing Deduplication

Depending on the use case, deduplication can be performed inline, meaning as data is first introduced or imported. This results in a reduced initial storage footprint, but the processing can become bottlenecked. Because of inline deduplication’s potential drain on computing power, using this method with storage that’s in everyday use is not recommended. 

Instead, deduplication can be performed retroactively as post-processing. With this method, redundant data is removed after ingestion. The advantage of this approach is that the operations can occur during off-hours or whenever the user specifies. Also, the user can direct the system to deduplicate files or data needed for a specific workload. Post-processing deduplication enables more flexibility but also requires larger available data storage than inline deduplication.

Data Deduplication vs. Compression vs. Thin Provisioning

Deduplication is often compared to or mixed up with compression and thin provisioning, which are two other methods for reducing amounts of storage. While deduplication eliminates and reduces the number of files or amount of data, compression uses algorithms to reduce the number of bits needed to record data. 

Thin provisioning is a technique of sourcing storage or compute resources from other sources on a network, such as other end users. In this way, existing resources are maximized, fewer are needed in total, and efficiency is increased.

What Is Veeam Deduplication?

Veeam Software is a U.S.-based developer of backup, disaster recovery, and modern data protection software for virtual, cloud-native, SaaS, Kubernetes, and physical workloads. Veeam Backup & Replication combines compression with deduplication to maximise storage savings across your system. 

What Is NTFS Deduplication?

New Technology File System (NTFS) is a proprietary journaling file system developed by Microsoft. NTFS deduplication conserves storage by eliminating the need to store excess copies of data, significantly increasing free storage capacity.

Best-in-class Data Reduction with Pure Storage

Data deduplication is just one piece of the larger data reduction puzzle. Not only does Purity Reduce on FlashArray™ boast a high-performance inline deduplication process with a variable block size of 4KB-32KB, but it also leverages pattern removal, inline compression, deep reduction, and copy reduction to deliver the most granular and complete data reduction ratios seen in the flash storage industry. Discover why data deduplication with Pure Storage® FlashArray is different.

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