JuiceFS

About JuiceFS

A high-performance, cloud-native file system driven by object storage. JuiceFS provides a POSIX-compatible interface backed by cloud storage like S3, making it easy to mount cloud storage as a local file system for data processing workloads.

Key Features

• 1POSIX-compatible distributed file system built on object storage (S3, GCS, Ceph)
• 2Metadata stored separately in Redis, TiKV, or PostgreSQL for fast access
• 3FUSE mount allows any POSIX application to access object storage as a local directory
• 4Transparent data encryption and compression on writes
• 5Hadoop-compatible interface for use with Spark and Hive

How Python Data Engineers Use JuiceFS

Python data engineers use JuiceFS to mount cloud object storage as a local POSIX file system — enabling Python pipeline code that reads and writes local files to work seamlessly with S3 or GCS as the backing store without using boto3 or cloud-specific SDKs. PySpark jobs on JuiceFS benefit from its Hadoop-compatible interface and local cache for repeated dataset reads.