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For most OpenZFS datasets, start with LZ4. It is the project’s broad default when CPU headroom and latency matter. Choose ZSTD when reducing storage consumption is more important and you can spend additional CPU; levels 3–7 are OpenZFS’s practical range. Keep GZIP mainly for existing configurations or a measured, rarely accessed archive where its slower operation is acceptable. These are starting points, not guarantees: your files, record size, sector size, storage, and workload determine the result. See the OpenZFS Compression documentation and Workload Tuning documentation.
Quick choice: which algorithm fits your dataset?
| Algorithm | Choose it when | What you trade | Default syntax |
|---|---|---|---|
| LZ4 | It is a general-purpose dataset, or latency and CPU headroom are priorities. | Very fast compression and decompression with a moderate ratio. | lz4 |
| ZSTD | Capacity savings matter more than the lowest possible CPU use. | More CPU work, with tunable levels from 1 (fastest) to 19 (highest compression). | zstd means zstd-3 |
| GZIP | You are maintaining an existing setup or have measured a special archival case. | Higher levels can be substantially slower; OpenZFS considers ZSTD a better new choice in most cases. | gzip means gzip-6 |
| Off | Content is already compressed or encrypted and another pass has no useful benefit. | You give up any compression of content that might still be compressible. | off |
OpenZFS summarizes the decision as “lz4 when latency and CPU matter, zstd (level 3–7) when capacity matters, off only for data that is already compressed or encrypted.” That guidance is workload-independent; measure before imposing one policy on every dataset.
What ZFS compression actually does
It is a per-dataset property
Compression is configured on each ZFS dataset and applied as records are written. ZFS attempts to store a compressed block only when the compressed representation saves enough space. A setting inherited from a parent can therefore affect a child dataset unless the child overrides it. The effective value on the dataset that receives the writes is what matters, not a pool-wide assumption. The property behavior and valid values are documented in zfsprops.7.
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Zero-filled blocks become holes
Every compression setting also recognizes an all-zero block and stores it as a hole rather than allocating physical sectors. This is independent of whether LZ4, ZSTD, or GZIP produces the best result for ordinary data. Sparse virtual-machine images and preallocated files can therefore show savings even when their non-zero portions are not especially compressible.
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Allocation granularity limits the visible benefit
Compressed blocks are rounded to whole sectors and must pass a minimum-saving threshold. OpenZFS’s example uses a 16 KiB record and 4 KiB sectors: the record occupies four sectors uncompressed, so compression must save at least 25 percent before it can occupy three sectors. A compressor can reduce the byte count without reducing the number of allocated sectors. This is why a laboratory ratio and the space reported by your pool can differ; see the explanation in the Compression documentation.
How LZ4, ZSTD, and GZIP differ
LZ4: the low-risk starting point
LZ4 is OpenZFS’s safe choice when you are uncertain. Its design favors fast compression and decompression, so it normally adds little latency and leaves more CPU available for applications, checksums, encryption, and other storage work. It does not expose a numeric compression-level property in ZFS. Use compression=lz4 when a dataset has mixed file types, interactive workloads, databases, active virtual machines, or simply an unknown future workload.
Fast does not mean ineffective. OpenZFS relays a historical LZ4-project test on the Silesia corpus that reported a 2.1:1 average LZ4 ratio. The page does not state a test year, and the corpus result is not a prediction for your files. Real ratios vary with content and allocation settings.
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ZSTD offers a broader speed-versus-ratio range. ZFS supports levels 1 through 19: lower levels favor speed, while higher levels spend more CPU to seek a smaller representation. The unqualified value zstd is level 3. OpenZFS recommends levels 3–7 as a practical capacity-oriented range rather than telling every user to select the maximum level.
Use ZSTD when storage capacity, replication volume, or backup footprint is worth additional write-time CPU and potentially higher latency. A level-3 setting is a conservative starting experiment; levels 5 or 7 can be evaluated on a less latency-sensitive archive. Higher levels are not automatically better: if data is rewritten frequently or the CPU is already saturated, the extra work can cost more than the saved sectors.
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GZIP: available, but usually a legacy or special-case choice
GZIP levels run from 1 through 9, and plain gzip means level 6. OpenZFS describes GZIP as much slower and says ZSTD generally offers similar or better ratios with better performance. Its higher ratio can still be relevant for data that is rarely read and will remain unchanged for a long time, provided you have measured the trade-off and accepted slower writes and reads.
The same OpenZFS workload-tuning page relays a historical Silesia-corpus result of 2.7:1 for gzip-1, compared with 2.1:1 for LZ4. The page identifies the LZ4 project as the tester but gives no year. These are named-corpus averages, not expected ZFS ratios; they also do not compare every GZIP level or account for ZFS’s sector-rounding threshold.
Decide using the workload, not a headline ratio
| Question | Favors | Why it matters |
|---|---|---|
| Is the workload latency-sensitive or CPU-constrained? | LZ4, or low-level ZSTD | Compression and decompression compete with application work and storage queues. |
| Is capacity, replication traffic, or backup size the dominant cost? | ZSTD, usually levels 3–7 | More CPU can be exchanged for fewer allocated sectors and fewer bytes transferred. |
| Are writes infrequent and reads rare? | A measured ZSTD level, occasionally existing GZIP | Write-time cost is paid less often, but read and recovery speed still matter. |
| Is the content JPEG, H.264/H.265, ZIP, software packages, or encrypted data? | Often off |
Those formats have already removed much redundancy; another pass may consume CPU without saving sectors. |
| Do you have a mixed dataset? | LZ4 or separate datasets | One property applies to all new records in that dataset; separate unlike workloads when their priorities differ. |
Do not promise a fixed compression ratio. File content, record size, sector size, storage media, deduplication and encryption choices, and the read/write pattern all influence the outcome. A compressor that wins on text can lose on media files, and a ratio that looks attractive may not reduce allocation because of sector rounding.
Check what your system is using now
The value on is not an algorithm name. On pools with the lz4_compress feature enabled, the current default resolves to LZ4; without that feature, it resolves to LZJB. New datasets have defaulted to on since OpenZFS 2.2.0, while older datasets retain their existing property values. Verify the actual dataset and its inherited value instead of assuming that every pool has the same behavior.
- Run
zfs get -r compression poolto display the compression property recursively, including datasets that inherit it. - Note whether the output is
on,off,lz4, a numbered ZSTD or GZIP value, or another supported value in your OpenZFS version. - Check the pool’s feature state if an inherited
onvalue does not explain the observed algorithm. The meaning ofondepends on the pool feature set and OpenZFS version.
Set an algorithm for new writes
Set the property on the dataset whose future writes should use the algorithm. These commands are examples; execute only the one that matches your decision.
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- Choose the target dataset, such as
pool/data, rather than changing an entire pool unintentionally. - Apply the setting:
zfs set compression=lz4 pool/data,zfs set compression=zstd pool/data,zfs set compression=zstd-5 pool/data, orzfs set compression=gzip-1 pool/archive. - Confirm the effective value with
zfs get compression pool/data. If the property is inherited elsewhere, inspect the recursive output as well. - Continue normal writes, then collect compression statistics after the dataset contains representative data. A setting change is not a retroactive conversion.
Use a numbered level only when you deliberately want that level. For example, zstd-5 is not interchangeable with plain zstd; the latter means level 3. Likewise, gzip-1 is a speed-oriented choice, while plain gzip means level 6.
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Read the dataset and pool ratios
After writing a realistic sample, inspect both the property and the reported ratios:
zfs get compression,compressratio,refcompressratio pool/data
zfs list -o name,used,logicalused,compressratio -r poolcompressratio includes descendants. refcompressratio reports the ratio for the referenced dataset itself, which is useful when child datasets would otherwise hide the parent’s behavior. Comparing logicalused with used translates the ratio into actual space consumed, although snapshots, metadata, reservations, and other dataset accounting can affect the relationship.
Use a controlled comparison
- Identify files that represent the real mix and access pattern: for example, database pages, virtual-machine disks, source trees, documents, or media, rather than a convenient but unrepresentative test file.
- Use separate test datasets or copies so each algorithm sees equivalent input. Keep record size, sector size, encryption choices, and storage hardware the same.
- Write the sample with LZ4, record CPU utilization, elapsed write time, logical and physical usage, and read behavior.
- Repeat with a selected ZSTD level and, only when there is a concrete reason, GZIP. Compare both capacity and application-visible latency.
- Allow enough data to pass through the normal workload. A few small files can be dominated by metadata and allocation rounding.
- Choose the setting that meets the workload’s actual constraint, not the one with the most impressive isolated ratio.
No generic figure can substitute for this test on your hardware. The historical Silesia numbers cited above are useful for understanding the algorithms’ direction, but OpenZFS does not present them as a guarantee for an individual dataset.
Changing compression does not convert old blocks
When you change the property, only newly written records use the new algorithm. Existing blocks remain in their current on-disk representation. Consequently, changing a busy dataset to ZSTD will not immediately reclaim space, and changing back to LZ4 will not make old ZSTD blocks faster to read.
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To obtain a new representation, rewrite or copy the data. Depending on your environment, that can include an application-level copy, a send/receive migration, or the zfs-rewrite facility identified by OpenZFS. Plan for the temporary space, I/O load, snapshot behavior, permissions, and downtime or consistency requirements of the method you select. Verify the new dataset’s ratios after the rewrite; the property change alone is not evidence that old data was transformed.
Important pitfalls and boundaries
Do not change recordsize solely to chase a ratio
Larger records can improve compression for some compressible data because the algorithm sees more context, but recordsize is a separate workload-tuning decision. Database pages, virtual-machine disks, and large sequential files can have different optimal record sizes. Change it for the workload’s I/O behavior, not just because a larger record could produce a better theoretical compression ratio.
Already-compressed and encrypted data may not shrink
JPEG, video codecs, archives, and encrypted streams generally contain little redundancy for a second compressor to remove. A second pass still consumes CPU and can add latency. OpenZFS’s practical guidance is to use off only for data that is already compressed or encrypted; apply that advice to a dataset whose contents are consistently of that kind, not to a mixed dataset that also contains compressible files.
Inherited properties can create surprises
A parent dataset can set compression for children through inheritance. A recursive inspection is therefore safer than checking only the pool root. If two workloads have different priorities, place them in separate datasets and set each property explicitly rather than relying on one inherited compromise.
Pool feature state and age matter
An old dataset may still show an older default even after an OpenZFS upgrade. The interpretation of on also depends on whether the pool has the lz4_compress feature. Record the OpenZFS version and inspect the actual property before documenting a standard for a fleet.
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Compression is not a substitute for backups
Compression reduces the representation of data; it does not provide an independent backup copy or protect against deletion, corruption, or an unavailable pool. Keep your normal snapshot, replication, and backup plan separate from the algorithm decision.
Practical choices by scenario
General file share with unknown growth
Use LZ4 first. It tolerates mixed content and keeps interactive access predictable. Revisit the choice only after measuring sustained storage pressure and CPU headroom on representative files.
Large document, source-code, or log archive
Test ZSTD at level 3, then levels 5–7 if the archive is capacity-focused and write latency is acceptable. Logs and text often have useful redundancy, but the actual ratio still depends on record and sector allocation.
Active database or virtual-machine dataset
Start with LZ4 unless measurement shows a clear capacity requirement. These workloads can be sensitive to latency and CPU contention, and their logical blocks may not compress uniformly.
Cold archive that is rarely read
A measured ZSTD level can be sensible when capacity dominates and writes are infrequent. GZIP should be selected only for an existing configuration or a test that demonstrates a worthwhile benefit despite its slower performance; OpenZFS considers ZSTD the preferred new alternative in most cases.
Dataset containing encrypted backups or media
Use off when the dataset is consistently made of already-compressed or encrypted objects. If it also contains ordinary documents or database dumps, separate those contents into datasets so that compressible data is not unnecessarily excluded.
Quick Recap
A concise operating checklist
- Inspect the effective property with
zfs get -r compression pool. - Confirm how your OpenZFS version and pool features interpret
on. - Choose LZ4 for the safest general starting point, or ZSTD when capacity justifies extra CPU.
- Use explicit levels: ZSTD 3–7 for the practical capacity range; GZIP 1–9 only for a measured or existing special case.
- Set the property on the target dataset, not reflexively on the entire pool.
- Remember that the change affects new writes only.
- Measure
compressratio,refcompressratio,used, andlogicalusedafter representative writes. - Account for sector rounding, the 25-percent threshold in the 16 KiB/4 KiB example, snapshots, and descendants when interpreting savings.
- Rewrite or copy existing data if it must receive a different on-disk representation.
- Document the workload, OpenZFS version, pool features, chosen level, and the measurements that justified the policy.
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