Data is changing at a scale never seen before — it lives in more places than ever and is growing in volume exponentially faster than the number of IT professionals tasked to manage it. Traditional forms of backup do not care how much storage is used as part of their processes. Today, however, with demands for backing up not only on-premises assets but also remote workforce devices and cloud workloads, many may face unique challenges as their backup footprint grows or retention requirements increase. Integrating separate third-party devices for data reduction and storage increases costs, management overheads and on-prem footprint, not to mention the risks of interoperability challenges.
Using a data reduction technique, such as deduplication, will help improve storage efficiency, reduce the strain on your network bandwidth for processes such as replication of data, and deliver reliable recoveries.
According to Cybersecurity Ventures, total global data storage is projected to exceed 200 zettabytes or 200,000,000,000,000,000,000,000 bytes by 2025.
What Is Data Deduplication?
Data deduplication or dedupe is a technique used to eliminate duplicate copies of repeating data. It is most effective when many copies of very similar or even identical data are present. Block redundancy is common in datasets such as test and dev environments, QA, virtual machines and virtual desktops. For example, similar if not identical blocks from common operating systems and application binaries across virtual environments.
How Does Data Deduplication Work?
Data deduplication works by examining similar byte patterns in data blocks or files. This helps ensure only one, unique copy of the data is stored while duplicate copies are linked to the unique data using a pointer. Deduplication can identify redundant copies of data across directories, data types, servers and locations.
In data deduplication, data is divided into several chunks. The way the chunks are divided may vary depending on the type of dedupe technique used. These chunks of data are then examined against other previous chunks. Each chunk is assigned a unique hash code. If the hash code of one chunk matches the hash code of the other, it is deemed to be a duplicate copy and is therefore eliminated.
For instance, consider a PowerPoint Presentation. A data deduplication system can recognize the unique data in a PPT and back it up accordingly. If you make certain changes to the deck and update it again, the system can distinguish the segments that have been modified and back up only those segments instead of the entire file. Even if you share the file with your colleagues, the system can identify the segments in both your and their email folders or hard drives (in case they have saved it locally) and will not back up these redundant copies.
Why Is Data Deduplication Important?
While storage capacities continue to increase at one end, the amount of data being created, used and stored is growing rapidly at the other end of the spectrum. Technologies, such as data deduplication, improves storage efficiency and reduces the amount of data that needs to be transmitted over the network. This not only enhances backup speed but also frees up space for additional files, which in turn leads to significant cost savings over time. By eliminating duplicate copies, dedupe optimizes storage capacity, increases on-appliance retention and reduces the landing zone space required for backups as well as the number of bytes that must be transferred between endpoints, e.g., the production asset and your backup appliance.
Today’s deduplication technology has evolved to keep pace with the rapid change in environments — even automating dedupe processes to improve backup and recovery performance.
Why Is Duplicate Data Bad?
Duplicate data is something organizations of all sizes must deal with constantly. If neglected, duplicated data accumulated over time can unnecessarily occupy precious storage space, wasting resources and driving up costs. Large amounts of duplicate data may result in poor data quality and inaccurate analytics.
Data Deduplication Pros and Cons
Data deduplication, also known as single-instance storage, offers multiple benefits in data backup and disaster recovery. However, it also has its drawbacks.
Advantages of Data Deduplication
Improved data quality: Data deduplication improves data quality by eliminating redundant or similar copies of data and ensuring that only a unique, single instance of data is stored.
Cost savings: By removing duplicate copies, dedupe maximizes storage capacity, which increases the purchase intervals of storage devices. This helps in saving a significant amount of money over time.
Better storage allocation: Data deduplication frees up storage space by removing redundant data, which would otherwise needlessly occupy valuable space.
Faster recoveries: Compared to non-deduped data, the volume of data that needs to be stored after deduplication is significantly less, which in turn reduces stress on network bandwidth and enables faster recovery of backed up data.
Meeting compliance regulations: By eliminating redundant copies, data deduplication improves data quality and helps in meeting compliance regulations.
Disadvantages of Data Deduplication
While there are many benefits of data deduplication, in the past, there were issues with duplicated hash codes being created by the original algorithm for generating hashes. Although rare, this did result in data loss. Improved algorithms have since resolved this problem and it isn’t a common issue or consideration in modern solutions anymore.
The idea of a single copy of data still scares some IT admins. Ideally, even a single data object stored in the production environment is protected by redundant copies i.e., backup copies or erasure coding.
Deduplication Versus Compression
People often misunderstand data deduplication and compression to be the same thing. However, these are two different techniques designed for different purposes.
Data deduplication is used to remove redundant data blocks. In this method, repeated data is eliminated so that only a single copy of the data is retained without manipulating or losing any critical information.
Data compression, on the other hand, removes redundant data at the binary level, which is the data within data blocks. This, in essence, reduces the size of a file by removing redundant data within the file. For example, a 100KB text file may be compressed to 54KB by removing redundant spaces and representing longer, common character strings with short representations by applying “pointers” or “markers.” In this process, the data is restructured and manipulated to reduce its size.
Deduplication tends to achieve better data reduction efficacy against smaller backup sets (the amount of data being backed up each time), while compression tends to achieve better results against larger data sets. Data compression reduces the overall size of files and makes their movement and storage more efficient.
Although designed for different purposes, when used in tandem, the two technologies can further increase efficiencies and reduce storage consumption and requirements.
Can You Perform Both Compression and Deduplication on the Same Data?
Yes, both compression and deduplication can be performed on the same data. Once data deduplication eliminates redundant copies of data, data compression that uses a formula or an algorithm can be performed to further compress the size of the data.
Data Deduplication Methods
There are several ways data deduplication can be performed. Different storage vendors utilize different dedupe approaches based on their backup solutions and needs. Some of the common dedupe techniques include:
Block-Level Versus File-Level:
Block-level data deduplication checks for redundant data blocks within a given data set. Only one original copy of each block is stored and subsequent copies are linked to the original copy. This method is highly efficient in virtual environments. When data in the block is altered, such as a file, only unique changes are stored.
File-level data deduplication checks for multiple identical files at the file level and stores only one unique copy. Redundant files are not stored but rather linked or pointed to the unique file.
Source-Based Versus Target-Based:
Source-based dedupe eliminates common blocks at the backup source (client or server) before data is sent over the network to the backup target.
In target-based deduplication, backups and data are sent over the network and land on the backup target. The backup target then performs the data deduplication.
Inline Versus Post-Processing:
Inline dedupe analyzes for redundant blocks while data is being written to the backup target. Duplicate copies are eliminated as they enter the storage environment and before data is written to disk. However, in post-processing, deduplication occurs after the backup has been ingested. Duplicate copies are removed once the backup has been written to disk.
Client-Side Versus Server-Side:
In client-side data deduplication, the backup-archive target and server work in tandem to identify duplicate data. Non-duplicate extents from the backup target are compared against the server being backed up.
In server-side data deduplication, the deduplication process occurs on the server once the data is backed up. This typically occurs in two phases – first by identifying the duplicate data and then by removing it by a server process such as reclaiming volumes in the primary storage pool or migrating data from the primary storage pool to another location.
Global Versus Custodial:
Global deduplication analyzes both the exactness and the digital fingerprint of data to remove redundant copies. This occurs against the entire backup set or across the entire volume.
Custodial deduplication, also referred to as “job-based” deduplication in some cases, removes redundant data within a job or “custodian.” For example, if Server/Custodian 1 has 10 similar copies of Data X, nine of those redundant copies are eliminated and only one is stored. If Server/Custodian 2 has the exact copy of Data X, those blocks will not be removed even though they are identical to the data on Server/Custodian 1.
Data Deduplication FAQs
Can Encrypted Data Be Deduplicated?
Yes, encrypted data can be deduplicated. Different storage vendors use different deduplication techniques for encrypted data. In some cases, they can use client-side deduplication to dedupe data blocks after encryption.
Unitrends uses replication as the underlying technology to first encrypt data and then compresses it on the on-premises appliance. The on-premises deduplication technology must decompress but can keep the data encrypted and still find blocks that can be deduplicated.
What Is the Difference Between Data Redundancy and Data Duplication?
Data redundancy refers to a situation when two or more fields of a database represent the same data. For instance, the name ‘Richard’ exists under a file called ‘Clients’ and the same name also exists in another file named ‘Orders.’ However, data duplication occurs when an exact copy of a file is created. For example, having two copies of a file named, “My Dog.jpg.”
What Is Deduplication Ratio?
According to TechTarget, a data deduplication ratio is the measurement of the data’s original size versus the data’s size after removing redundancy. For example, a 10:1 deduplication ratio implies that 10 units of deduped data are stored in 1 unit of storage device. The deduplication ratio differs depending on the type of data deduplication technique applied and the type of data.
Deduplication in Backup
As data continues to grow rapidly, effective utilization of storage solutions and resources are critical for quick access to critical information and instant recovery. Data deduplication can help you enhance your backup strategy by maximizing storage capacity and efficiency while also saving you significant costs in the long run. Dedupe improves data quality and hygiene, helps in meeting compliance requirements and in strategic decision-making.
Take Control of Your Data With Unitrends
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