Skip to main content

Erasure Coding

· 3 min read

Erasure coding is a critical method used in data storage systems to enhance data durability and availability, surpassing traditional techniques like mirroring in storage efficiency. This blog post explores what erasure coding is, how it operates, and its significant role in modern storage environments.

What is Erasure Coding?

Erasure coding is a data protection technique utilized in distributed systems and storage networks. It involves breaking down data into multiple fragments, enhancing these with redundant data pieces, and dispersing them across various locations or storage media. Its primary advantage is the ability to reconstruct the original data from a subset of the available fragments, even if some are lost or corrupted.

How Erasure Coding Works

Consider a basic example of erasure coding, using a configuration often referred to as (4,2). In this setup, a file is divided into four data pieces (D1, D2, D3, D4), and two additional redundant pieces (R1, R2) are created. These redundant pieces are derived using mathematical algorithms that involve polynomial or matrix calculations, typically within finite field arithmetic.

The (4,2) configuration indicates that any four out of the six pieces (four data and two redundant) can be used to reconstruct the original file. This arrangement allows the system to manage up to two pieces of lost or corrupted data without affecting the data's integrity.

Benefits of Erasure Coding

  • Storage Efficiency: Erasure coding is more storage-efficient than traditional replication methods. For example, triple replication incurs a 200% overhead, while a (10,4) erasure coding configuration might offer similar protection levels with reduced overhead.
  • Scalability: Erasure coding scales more effectively than RAID or mirroring, especially suitable for large-scale environments such as those found in cloud storage and big data applications.
  • Fault Tolerance: This coding method can tolerate multiple simultaneous failures, ensuring data availability and integrity, crucial in environments where continuous data access is mandatory.

Applications of Erasure Coding

  • Cloud Storage: Major cloud providers like Google and Microsoft implement erasure coding to secure data in their cloud platforms, allowing them to use storage space more efficiently and safeguard against significant data center failures.
  • Big Data Platforms: Distributed computing systems like Apache Hadoop and Apache Spark use erasure coding to minimize storage overhead while maintaining necessary fault tolerance.
  • Object Storage Systems: Object storage, managing vast amounts of unstructured data, often uses erasure coding to strike an optimal balance between redundancy and storage costs. Systems such as Ceph and Swift are examples where erasure coding is integral to their storage strategy.


Erasure coding stands as an effective strategy in data protection, enabling data reconstruction from partial fragments and ensuring robust solutions for data integrity and availability. As data volumes and their criticality increase, erasure coding will continue to be a key component in storage strategies across various sectors.