What Is Delta Encoding?

From social media interactions to scientific simulations, data underpins nearly every facet of our lives. With the growing digital data proliferation, the efficient management, storage, and transmission of information have become critical priorities for businesses and individuals alike. One key technique that addresses these challenges is delta encoding.

Delta encoding is a methodical approach to data management that focuses on the changes or differences between successive pieces of data rather than the entirety of the data itself. This approach enables more efficient use of storage resources and facilitates faster data transmission over networks.

In this article, we explore the concept of delta encoding, how it works, its applications, and the advantages and limitations it presents.

What Is Delta Encoding?

Delta encoding, also referred to as delta compression or data differencing, is a technique for storing or transmitting data. Instead of directly storing the entire data set, it calculates and stores the differences between consecutive data points. The name itself reflects this principle, as the Greek letter delta (Δ) signifies change. The main purpose of this technique is to optimize storage space and reduce bandwidth usage by capturing and representing only the differences (or deltas) between sequential data points.

To illustrate this concept, let's consider a simple sequence of numbers: [10, 15, 20, 25]. Suppose a system is to store the sequence; instead of storing each data point as it is, delta encoding would capture and represent the changes between each number and its predecessor:

• The difference between 15 and 10 is +5.

• The difference between 20 and 15 is +5.

• The difference between 25 and 20 is +5.

Therefore, using delta encoding, we would store or transmit [10, +5, +5, +5]. This representation efficiently communicates the incremental changes within the sequence rather than redundantly transmitting the entire sequence of numbers.

How Does Delta Encoding Work?

Delta encoding follows a straightforward, three-step process of capturing and representing the differences between consecutive data points:

1. Identify consecutive data points
   
   The first step in delta encoding is identifying the sequence of data points that need to be encoded. These data points could represent anything from numerical values in a data set to pixels in an image or frames in a video.

2. Compute delta valuesOnce the data points are identified, delta encoding calculates the difference (delta) between each consecutive pair of data points. The mathematical calculation for the delta value is:
   
   Delta Value = Current Data Point - Previous Data Point
   
   For instance, if the current data point is 25 and the previous data point is 20, the delta value would be +5. That is, 25 - 20 = 5.

3. Store or transmit delta values

After computing the delta values for the entire sequence of data points, the resulting delta values are stored or transmitted instead of the original data points. This is because the receiver already has the previous data point (20) based on the transmission order. By adding the delta value (5) to the previous data point, the receiver can easily reconstruct the original data point (25 + 20 = 25). This approach significantly reduces the amount of data that needs to be stored or transmitted, particularly in scenarios where the changes between data points are relatively small or incremental.

Applications of Delta Encoding

Delta encoding's ability to reduce data size and improve transmission efficiency makes it a valuable technique for data storage and transmission across various industries. Here are some prominent applications:

• Video streaming: Video sequences are perfect candidates for delta encoding. When multiple frames of a video are short with little changes in the background, delta encoding only takes into account the new changing pixels in the video, which are transmitted and then added to a previous frame to make the full frame. This targeted approach significantly reduces the bandwidth required for streaming, allowing for smoother playback and efficient use of network resources.
• Version control systems: Software development heavily relies on version control systems like Git. These systems track changes made to files over time. Delta encoding plays a crucial role here. Instead of storing entire new versions of a file with minor modifications, only the differences between those versions are stored. This minimizes storage requirements and allows developers to efficiently track the evolution of their code.
• Network protocols: Real-time communication protocols like Real-time Transport Protocol (RTP) often utilize delta encoding for audio and video transmission. By focusing on the changes between audio samples or video frames, delta encoding optimizes data transfer, ensuring smooth and uninterrupted communication during calls or video conferences.
• Data backup: Data backups are essential for protecting valuable information. Delta encoding can be employed to store only the changes made to data since the last backup. This significantly reduces the amount of data that needs to be backed up, saving storage space and minimizing backup times.
• Software updates: Distributing software updates is another area where delta encoding shines. Instead of downloading the entire new software version, users can receive only the differences between the existing version and the update. This translates to faster downloads and reduced bandwidth consumption, improving the overall update experience.

Benefits of Delta Encoding

Delta encoding offers several compelling advantages in terms of data storage and transmission efficiency, making it a valuable technique across various applications. Let's delve into the key benefits of using delta encoding:

• Reduction of redundancy: One of the primary advantages of delta encoding is its ability to reduce redundancy in data storage and transmission. By focusing on capturing and representing only the differences between consecutive data points, delta encoding eliminates the need to store or transmit unchanged data repeatedly. This minimizes storage requirements and conserves network bandwidth, especially in scenarios where data changes incrementally over time.
• Optimization of data transfer: Delta encoding optimizes data transfer by transmitting only the essential changes between data points or versions. In applications such as version control systems and file synchronization, delta encoding facilitates the efficient transfer of file modifications without transmitting entire files. This approach significantly reduces the amount of data transmitted over networks, leading to faster transfer speeds and improved overall network performance.
• Storage space efficiency: Delta encoding enables efficient storage space utilization by storing only the differences (or deltas) between data points. Instead of maintaining multiple copies of similar data, delta encoding focuses on capturing incremental changes, resulting in reduced storage overhead and more economical use of storage resources. This efficiency is particularly beneficial in environments with limited storage capacity or high data volume.
• Data compression and backup efficiency: Delta encoding contributes to effective data compression and backup strategies by enabling incremental backups and updates. In data backup scenarios, delta encoding allows for efficient storage of backup data by capturing only the changes made since the last backup, reducing backup time and storage requirements.
• Enhanced version control: In version control systems, delta encoding supports efficient version management by enabling selective storage and retrieval of file changes. Instead of storing complete copies of files for each version, delta encoding stores and transmits only the modifications, enabling users to track and manage version histories effectively. This streamlined approach to version control simplifies collaboration and accelerates software development processes.
• Streamlined data synchronization: Delta encoding facilitates smooth and efficient data synchronization by transmitting only the differences between data sets or versions. This is particularly valuable in distributed computing environments, where data synchronization across multiple devices or systems is essential. Delta encoding optimizes data synchronization processes, ensuring consistency and coherence across distributed data sources.

Challenges and Limitations

While delta encoding offers numerous advantages, it's important to acknowledge its limitations. Here are some key challenges in the use of this technique:

• High processing overhead: Delta encoding requires additional processing to calculate and apply delta values between consecutive data points. In scenarios where frequent updates or changes occur, the computational overhead of delta encoding can become significant, impacting system performance and responsiveness. Complex data structures or large data sets may exacerbate this processing burden.
• Baseline dependence: The effectiveness of delta encoding heavily relies on the initial baseline value. If the data exhibits significant changes at the outset, the delta values might become large. This negates the compression benefit, as large delta values require just as many bits to store as the original data points. Imagine a temperature reading that suddenly jumps from 10°C to 50°C. The delta value (40°C) would be quite large, offering minimal compression in this scenario.
• Unsuitable for random data: Delta encoding thrives on predictable changes between consecutive data points. For random data with no clear pattern or correlation, the delta values might be similar in size to the original data points. This scenario offers minimal compression benefit. Imagine a sequence of random numbers with no discernible pattern. The delta between each number might be just as random, making delta encoding ineffective.
• Decoding requirements: While encoding is straightforward, the receiving end needs to possess the original baseline value to decode the delta-encoded data. This can be a challenge in certain scenarios. For example, if a delta-encoded video stream is transmitted without including the first frame (the baseline), the receiver wouldn't be able to reconstruct the subsequent frames accurately.
• Limited compression for similar data: Delta encoding might not offer significant compression when dealing with data sets where consecutive values are very similar. Imagine a long sequence of identical numbers. The delta values between them would all be zero, requiring storage space just like the original data.
• Complexity in error handling and recovery: Delta encoding introduces complexities in error handling and recovery, particularly in environments where data integrity and consistency are critical. In cases of data corruption or transmission errors, recovering the original data from delta-encoded representations may require sophisticated error detection and correction mechanisms, adding complexity to data recovery processes.

Conclusion

Delta encoding plays a vital role in modern data management and transmission. By focusing on changes rather than complete data sets, it optimizes storage efficiency and accelerates data transfer speeds. By leveraging delta encoding alongside other data reduction techniques offered by solutions like Pure Storage® FlashArray™ and FlashBlade®, organizations can significantly reduce storage costs and optimize data handling.