# ZFS Compression

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How to install ZFS and enable system-level compression for QuestDB.

:::warning Use Parquet for compression

The preferred way to compress QuestDB data is to convert partitions to
[Parquet](/docs/concepts/parquet/#data-compression). QuestDB compresses Parquet
partitions natively and keeps them fully queryable, with no file system
requirements. In QuestDB Enterprise, a
[storage policy](/docs/concepts/storage-policy/) converts partitions
automatically as they age, and can also tier them to object storage. In QuestDB
open source, convert partitions manually with
[`ALTER TABLE CONVERT PARTITION`](/docs/concepts/parquet/#converting-to-parquet).

ZFS compression works at the file system level, outside the database. This page
remains for existing deployments that already run on ZFS.

:::

QuestDB can use [ZFS](https://openzfs.org/wiki/Main_Page) for system-level
compression, reducing disk usage without application changes.

The following example shows how to set up ZFS on Ubuntu:

```bash title="Ubuntu - Install ZFS"
sudo apt update
sudo apt install zfsutils-linux
```

To enable compression, create a ZPool with compression enabled:

```bash title="Ubuntu - Enable compression"
zpool create -m legacy -o feature@lz4_compress=enabled -o autoexpand=on -O compression=lz4 -t volume1 questdb-pool sdf
```

The exact commands depend on which version of ZFS you are running. Use the
[ZFS docs](https://openzfs.github.io/openzfs-docs/man/master/8/zpool-create.8.html)
to customize your ZFS to meet your requirements.

Once created, ZFS provides system-level compression.

## Compression choices, LZ4 and zstd

ZFS offers a number of compression choices when constructing the volume.

[LZ4](https://github.com/lz4/lz4) offers a good balance of compression ratio versus increased CPU usage, and slowed performance. For general usage, we recommend using LZ4.

[zstd](https://github.com/facebook/zstd) is another strong option. This will provide higher compression ratios, but take longer to decompress. We recommend this when storage size is an absolute priority, or for embedded-style deployments (i.e. Raspberry Pi, home IoT setups).

As always, it is best to benchmark your choice to ensure that the performance matches your use case.

:::note
We regularly test ZFS with LZ4 compression. If you encounter issues with other
compression algorithms, please let us know.
:::