Compression
ZFS offers transparent compression, meaning that data is compressed before being written to disk and decompressed automatically when read. Compression can significantly reduce storage space usage and, in some cases, improve performance by reducing the amount of data that needs to be written to and read from disk.
Available Compression Algorithms
ZFS supports several compression algorithms, each optimized for different workloads. The following are the primary compression algorithms available:
| Algorithm | Description | Compression Ratio | Performance | Use Case |
|---|---|---|---|---|
lz4 | High-speed compression with a balance of performance and ratio. | Moderate (2:1) | Fast compression and decompression. | General-purpose workloads, logs, databases, etc. |
lzjb | Older algorithm, predecessor of lz4. | Moderate (similar to lz4) | Slower than lz4, but suitable for legacy systems. | Legacy systems or backward compatibility. |
zle | Compresses zero-filled blocks. | High, but only for zero-filled blocks. | Minimal performance impact. | Virtual machine images and datasets with zero-filled blocks. |
gzip | Offers compression levels from gzip-1 to gzip-9, with varying performance. | High (up to 10:1) | Slower, with higher CPU usage. | Archival data, backups, where storage efficiency is critical. |
zstd | Newer algorithm, faster than gzip with better ratios. | High | Faster than gzip, moderate CPU usage. | Suitable for archival data and large files. |
lz4
Description: lz4 is a high-speed compression algorithm that provides a good balance between compression ratio and performance. It is the default and most recommended algorithm for general-purpose use.
Compression Ratio: Moderate (typically 2:1).
Performance: Fast compression and decompression.
Use Case: Suitable for most workloads, especially when low CPU overhead and fast performance are required. Ideal for datasets where compression benefits are moderate but speed is important.
lzjb
Description: lzjb is an older, lightweight compression algorithm that was used by ZFS before lz4 became the default.
Compression Ratio: Moderate (similar to lz4, but slightly less efficient).
Performance: Good for legacy systems but generally slower and less efficient than lz4.
Use Case: Typically used for older systems that may not support newer algorithms or where backward compatibility is required.
zle (Zero-Length Encoding)
Description: zle is a simple compression algorithm that compresses blocks filled with zeroes. It is useful in environments where many zero-filled blocks are written.
Compression Ratio: High, but only effective with zero-filled data.
Performance: Minimal impact on performance.
Use Case: Used in scenarios like virtual machine images where zero-filled blocks are common.
gzip
Description: The gzip compression algorithm offers various levels of compression (gzip-1 to gzip-9), with gzip-9 providing the highest compression ratio but also the most CPU overhead.
Compression Ratio: High (up to 10:1 in some cases).
Performance: Slower compression and decompression compared to lz4, with higher CPU usage.
Use Case: Best suited for archival data, backups, and datasets where maximizing storage efficiency is more important than real-time performance. The gzip algorithm is configurable with levels ranging from 1 (fastest) to 9 (most space-saving).
zstd (Zstandard)
Description: zstd is a relatively new compression algorithm designed to offer faster compression speeds and better compression ratios than gzip. It provides different levels of compression, similar to gzip.
Compression Ratio: High, with better performance than gzip.
Performance: Faster than gzip, but still has a moderate CPU overhead.
Use Case: Suitable for scenarios requiring a balance between compression ratio and performance, often used for archival data and large files.
Choosing the Right Compression for Your Data
When selecting a compression algorithm for a dataset, several factors should be considered to achieve the optimal balance between performance and storage efficiency.
Workload Type
For general-purpose workloads, lz4 is recommended due to its low overhead and good balance between compression ratio and performance. It is ideal for databases, logs, and most file systems where real-time performance is important.
For archival or backup purposes, where compression ratio is prioritized over speed, gzip-9 or zstd are better choices. These algorithms offer a higher compression ratio at the cost of slower writes and higher CPU usage.
Data Characteristics
If the dataset contains many zero-filled blocks, such as in virtual machine images or sparse files, zle can be used to eliminate unnecessary disk space usage without significant computational overhead.
For text-based files, backups, and logs that compress well, gzip** or **zstd` can save significant storage space at the cost of slower write speeds.
System Resources
In systems with limited CPU resources, enabling gzip-9 can affect overall performance. In such cases, lz4 is preferred to avoid excessive CPU usage.
In systems with ample CPU resources where storage efficiency is more critical, gzip-9 or zstd can be used for compressing archival or infrequently accessed data.