JuiceFS is a high-performance distributed file system designed for the cloud. And JuiceFS Cloud Service is a SaaS (Software-as-a-Service) solution provided by Juicedata. Unlike the open-source edition of JuiceFS, it is shipped with an in-house developed, high-performance metadata engine, so your team can use and manage JuiceFS storage more easily.
JuiceFS is designed for high-performance computing needs, commonly utilized in AI & machine learning for training, inference, model distribution, as well as in big data processing and analysis. Within industries such as generative AI, autonomous driving, quantitative trading, and bioinformatics, JuiceFS serves as a unified storage solution in users' data pipelines. It efficiently manages column-based structured data, semi-structured data like CSV and JSON, and various forms of unstructured data used for computation, including videos, images, and audio files.
JuiceFS separates "data" and "metadata" storage. Files are split into chunks and stored in Amazon S3 to enhance storage performance, while metadata (directories,file names) is stored in our fully managed service. The built-in caching capabilities of JuiceFS can significantly improve I/O throughput by utilizing the local storage of computing nodes, while also substantially reducing the bandwidth overhead of S3. With full POSIX compatibility, it enables S3 to be utilized as massive local disks, allowing them to be mounted and accessed on different hosts across platforms and regions.
Highlights
JuiceFS provides interfaces compatible with POSIX, HDFS, and S3, serving as a unified storage solution for AI job pipelines, thereby reducing unnecessary data copying and migration efforts.
JuiceFS enhances I/O efficiency through caching, prefetching, and concurrent reading. Its high-performance metadata service efficiently manages millions of requests per second, ensuring response times from milliseconds to hundreds of microseconds. For read-intensive tasks like model training, it uses multi-level caching to speed up data access, scaling read throughput to hundreds of gigabytes per second.
The metadata service and object storage of JuiceFS can meet the concurrent demands of thousands to tens of thousands of clients. The automatic caching feature of the JuiceFS client can significantly reduce the load on the metadata service and object storage during model training, further enhancing the overall capacity of the storage system.
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This listing offers one pricing option, the Professional unit. You pay per GiB of stored data each month, so your cost scales directly with how much data you keep. There is no upfront commitment; billing follows a pay-as-you-go model based on usage. This unit supports capacity up to 10 PiB, 100 million inodes, and 1000 connected clients. As your stored data grows within these limits, your monthly charge grows in step with it.
Top-of-mind questions for buyers
How is the per-GiB charge measured — by stored data, and does metadata count?
You are billed per GiB of file data stored each month. The service separates data from metadata. Files are split into chunks stored in object storage, while directories and file names are tracked in the managed metadata engine. Your charge scales with the amount of file data you keep.
Do I commit upfront, or does billing follow actual usage each month?
Billing follows a pay-as-you-go model with no upfront commitment. You pay for the GiB you store each month, so cost rises and falls with your stored data. This suits workloads where storage volume changes over time rather than staying fixed.
What are the capacity limits, and what happens as my file count or clients grow?
The Professional unit supports up to 10 PiB of data, 100 million inodes, and 1000 connected clients. Your monthly charge grows with stored data within these limits. Inodes track files and directories; clients are servers mounting the file system. Contact the vendor for needs beyond these limits.
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