JuiceFS is a high-performance POSIX file system released under Apache License 2.0, mainly designed for the cloud-native environment. The data, stored via JuiceFS, will be persisted in object storage (e.g. Amazon S3), and the corresponding metadata can be persisted in various database engines such as Redis, MySQL, and TiKV based on the scenarios and requirements.
With JuiceFS, massive cloud storage can be directly connected to big data, machine learning, artificial intelligence, and various application platforms in production environments. Without modifying code, the massive cloud storage can be used as efficiently as local storage.
Document: Quick Start Guide
- Fully POSIX-compatible: Use as a local file system, seamlessly docking with existing applications without breaking business workflow.
- Fully Hadoop-compatible: JuiceFS’ Hadoop Java SDK is compatible with Hadoop 2.x and Hadoop 3.x as well as various components in the Hadoop ecosystems.
- S3-compatible: JuiceFS’ S3 Gateway provides an S3-compatible interface.
- Cloud Native: A Kubernetes CSI Driver is provided for easily using JuiceFS in Kubernetes.
- Shareable: JuiceFS is a shared file storage that can be read and written by thousands of clients.
- Strong Consistency: The confirmed modification will be immediately visible on all the servers mounted with the same file system.
- Outstanding Performance: The latency can be as low as a few milliseconds, and the throughput can be expanded nearly unlimitedly (depending on the size of the object storage). Test results
- Data Encryption: Supports data encryption in transit and at rest (please refer to the guide for more information).
- Global File Locks: JuiceFS supports both BSD locks (flock) and POSIX record locks (fcntl).
- Data Compression: JuiceFS supports LZ4 or Zstandard to compress all your data.
JuiceFS consists of three parts:
- JuiceFS Client: Coordinates object storage and metadata storage engine as well as implementation of file system interfaces such as POSIX, Hadoop, Kubernetes, and S3 gateway.
- Data Storage: Stores data, with supports of a variety of data storage media, e.g., local disk, public or private cloud object storage, and HDFS.
- Metadata Engine: Stores the corresponding metadata that contains information of file name, file size, permission group, creation and modification time and directory structure, etc., with supports of different metadata engines, e.g., Redis, MySQL, SQLite and TiKV.
JuiceFS can store the metadata of file system on Redis, which is a fast, open-source, in-memory key-value data storage, particularly suitable for storing metadata; meanwhile, all the data will be stored in object storage through JuiceFS client. Learn more
Each file stored in JuiceFS is split into “Chunk” s at a fixed size with the default upper limit of 64 MiB. Each Chunk is composed of one or more “Slice”(s), and the length of the slice varies depending on how the file is written. Each slice is composed of size-fixed “Block” s, which are 4 MiB by default. These blocks will be stored in object storage in the end; at the same time, the metadata information of the file and its Chunks, Slices, and Blocks will be stored in metadata engines via JuiceFS. Learn more
When using JuiceFS, files will eventually be split into Chunks, Slices and Blocks and stored in object storage. Therefore, the source files stored in JuiceFS cannot be found in the file browser of the object storage platform; instead, there are only a chunks directory and a bunch of digitally numbered directories and files in the bucket. Don’t panic! This is just the secret of the high-performance operation of JuiceFS!
Before you begin, make sure you have:
- Redis database for metadata storage
- Object storage for storing data blocks
- JuiceFS Client downloaded and installed
Please refer to Quick Start Guide to start using JuiceFS right away!
Check out all the command line options in command reference.
It is also very easy to use JuiceFS on Kubernetes. Please find more information here.
If you wanna use JuiceFS in Hadoop, check Hadoop Java SDK.
- Redis Best Practices
- How to Setup Object Storage
- Cache Management
- Fault Diagnosis and Analysis
- FUSE Mount Options
- Using JuiceFS on Windows
- S3 Gateway
Please refer to JuiceFS Document Center for more information.
JuiceFS has passed all compatibility tests (8813 in total) in the latest pjdfstest .
All tests successful. Test Summary Report ------------------- /root/soft/pjdfstest/tests/chown/00.t (Wstat: 0 Tests: 1323 Failed: 0) TODO passed: 693, 697, 708-709, 714-715, 729, 733 Files=235, Tests=8813, 233 wallclock secs ( 2.77 usr 0.38 sys + 2.57 cusr 3.93 csys = 9.65 CPU) Result: PASS
Aside from the POSIX features covered by pjdfstest, JuiceFS also provides:
- Close-to-open consistency. Once a file is written and closed, it is guaranteed to view the written data in the following open and read. All the written data can be read immediately within the same mount point.
- Rename and all other metadata operations are atomic, guaranteed by Redis transaction.
- Opened files remain accessible after unlink from same mount point.
- Mmap (tested with FSx).
- Fallocate with punch hole support.
- Extended attributes (xattr).
- BSD locks (flock).
- POSIX record locks (fcntl).
JuiceFS provides a subcommand that can run a few basic benchmarks to help you understand how it works in your environment:
The figure above shows that JuiceFS can provide 10X more throughput than the other two (see more details).
The result shows that JuiceFS can provide significantly more metadata IOPS than the other two (see more details).
There is a virtual file called
.accesslog in the root of JuiceFS to show all the details of file system operations and the time they take, for example:
$ cat /jfs/.accesslog 2021.01.15 08:26:11.003330 [uid:0,gid:0,pid:4403] write (17669,8666,4993160): OK <0.000010> 2021.01.15 08:26:11.003473 [uid:0,gid:0,pid:4403] write (17675,198,997439): OK <0.000014> 2021.01.15 08:26:11.003616 [uid:0,gid:0,pid:4403] write (17666,390,951582): OK <0.000006>
The last number on each line is the time (in seconds) that the current operation takes. You can directly use this to debug and analyze performance issues, or try
juicefs profile /jfs to monitor real time statistics. Please run
juicefs profile -h or refer to here to learn more about this subcommand.
- Amazon S3
- Alibaba Cloud Object Storage Service (OSS)
- Tencent Cloud Object Storage (COS)
- Qiniu Cloud Object Storage (Kodo)
- Google Cloud Storage
- Azure Blob Storage
- QingStor Object Storage
- Ceph RGW
- Local disk
JuiceFS supports almost all object storage services. Learn more.
JuiceFS is production ready and used by thousands of machines in production. A list of users has been assembled and documented here. In addition, JuiceFS has several collaborative projects that integrate with other open-source projects, which we have documented here. If you are also using JuiceFS, please feel free to let us know, and you are welcome to share your specific experience with everyone.
The storage format is stable, and will be supported by all future releases.
- Support FoundationDB as metadata engine
- Directory quotas
- User and group quotas
- Write once read many (WORM)
Thank you for your contribution! Please refer to the JuiceFS Contributing Guide for more information.
JuiceFS collects anonymous usage data by default to help us better understand how the community is using JuiceFS. Only core metrics (e.g. version number) will be reported, and user data and any other sensitive data will not be included. The related code can be viewed here.
You could also disable reporting easily by command line option
juicefs mount --no-usage-report
JuiceFS is open-sourced under Apache License 2.0, see LICENSE.