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// file-systems-storage
Distributed file systems and storage solutions for large-scale data.
Distributed file systems and storage solutions provide the foundation for storing and accessing massive datasets across clusters of machines. These systems are designed to handle petabytes of data with high throughput, fault tolerance, and horizontal scalability. From the Hadoop Distributed File System (HDFS) that pioneered big data storage to modern cloud-native solutions, these tools enable data engineers to reliably store raw data, intermediate processing results, and final outputs across distributed infrastructure.
| Tool | Pricing | Rating | |
|---|---|---|---|
HD HDFSfeatured Hadoop Distributed File System | Free | ★ 4.4 | → |
AL Alluxio Memory-Centric Storage System | Freemium | ★ 4.2 | → |
CE CEPH Unified Distributed Storage | Free | ★ 4.4 | → |
JU JuiceFSnew Cloud-Native File System | Freemium | ★ 4.3 | → |
GL GlusterFS Scalable Network File System | Free | ★ 4.0 | → |
SE SeaweedFSnew Simple Distributed File System | Free | ★ 4.2 | → |
S3 S3QL Cloud-Backed File System | Free | ★ 3.8 | → |
LI LizardFS Fault-Tolerant Distributed File System | Free | ★ 3.7 | → |
Choose HDFS if you are running a Hadoop ecosystem and need tight integration with MapReduce, Spark, and Hive. For cloud-native storage, AWS S3 and Google Cloud Storage offer virtually unlimited scalability with pay-per-use pricing. Use Alluxio as a caching layer to accelerate access to data stored in slower storage systems. CEPH provides a unified storage solution supporting object, block, and file storage. JuiceFS is ideal when you need a POSIX-compatible file system backed by cloud object storage.
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