Why JuiceFS?
Management of tens of billions of files
JuiceFS can efficiently handle tens of billions of files, making it ideal for managing genomic data, protein structures, microscopy images, and other large-scale datasets with high storage and retrieval efficiency.
Low-latency data access
By separating performance from capacity, JuiceFS leverages NVMe caching near compute nodes to significantly enhance read and write speeds. This meets the low-latency data access demands of workflows like molecular dynamics simulations and genome sequence analysis.
Cost-effective performance
JuiceFS' architecture delivers high-performance storage without relying on expensive hardware, striking a balance between performance, capacity, and cost to help enterprises optimize their budgets.
Comprehensive support for biotech orchestration tools
JuiceFS is fully compatible with widely used orchestration tools in genomics and other biotech workflows, including Nextflow, Cromwell, and Slurm.
Global deployment and collaboration
JuiceFS supports data mirroring and synchronization across multi-cloud environments, enabling biotech companies to access data seamlessly worldwide while optimizing cross-region data transfer costs and latency.
Open source
JuiceFS Community Edition is available under the Apache 2.0 license, allowing enterprises to adapt it flexibly to meet their specific needs.
Feature Overview
MemVerge Chose JuiceFS: Small File Writes 5x Faster than s3fs
In bioinformatics workflows using Nextflow, the performance of shared storage systems is critical to efficiency. JuiceFS offers a high-performance shared storage solution, particularly excelling at managing large numbers of small files. Tests reveal that JuiceFS’ write speed is five times faster than s3fs, and its superior cost-efficiency makes it a preferred choice for processing complex bioinformatics datasets. [Learn more]
DP Technology: Optimizing Massive Small File Storage for Molecular Docking
Molecular docking generates massive data demands, especially for small files. For instance, one docking experiment produced approximately 600 million small files totaling 2.3 TB uncompressed (1.5 TB compressed), with an average file size of 4 KB. JuiceFS supports files of all sizes and demonstrates exceptional performance when handling small files. Its full POSIX compatibility also makes it ideal for AI workflows, particularly systems running Python-based services. [Learn more]