ARCHIL
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Archil vs JuiceFS

Pick JuiceFS for open source you run yourself on almost any storage, if a bucket of JuiceFS chunks is fine. Pick Archil when files must stay readable objects in your S3, GCS or R2 bucket, with no metadata engine to run and whole-disk branches in milliseconds.

Where Archil stands out

  • Files stay readable in your bucket

    Each file is an ordinary object at its path; JuiceFS stores blocks under a chunks folder.

  • Nothing to operate

    No metadata database to provision, back up or scale.

  • Whole-disk branches

    Branch a whole disk in tens of milliseconds; JuiceFS clones are per file or directory and not atomic for directories.

Archil and JuiceFS, side by side

What it is
Archil: Managed POSIX file system with an S3 API, plus Firecracker sandboxes
JuiceFS: Open-source distributed POSIX file system; managed Cloud Service and Enterprise Edition
Parts you run
Archil: The Archil client only
JuiceFS: Client plus a metadata engine (Redis, PostgreSQL, MySQL, TiKV and others) in Community Edition; Juicedata runs it in Cloud Service
Data in the bucket
Archil: Ordinary objects at their paths, on synced disks
JuiceFS: Blocks under a chunks folder; mapping in the metadata engine
Use an existing dataset in place
Archil: Yes: point a disk at the bucket
JuiceFS: No: write it through JuiceFS first
S3 access
Archil: Every disk is a strongly consistent S3 bucket
JuiceFS: S3 Gateway (built on MinIO) in front of a volume
Many clients at once
Archil: Yes, up to 5,000 per disk
JuiceFS: Yes, thousands of servers
Snapshots and branches
Archil: Whole-disk checkpoint p50 13 ms, branch p50 33 ms, any size
JuiceFS: juicefs clone per file or directory; directory clones aren't atomic
Shared cache
Archil: SSD storage layer shared by every client
JuiceFS: Local per client; distributed in Enterprise and Cloud
Supported storage
Archil: S3, GCS, R2, S3-compatible, or Archil-managed
JuiceFS: 40+ backends, including S3, GCS, Azure Blob, R2, MinIO, Ceph and HDFS
Licensing
Archil: Managed service
JuiceFS: Community Edition Apache 2.0; Cloud and Enterprise commercial

Measured on one EC2 host

npm ci finished in 12.4 s on Archil, 4.3x faster than JuiceFS in writeback mode (53.8 s) and close to local disk (10.7 s). git clone was closer: 19.8 s on Archil, 29.2 s on JuiceFS writeback.

MethodOne AWS c7gn.2xlarge (arm64) in us-east-1, every file system mounted on the same host. Archil client 0.10.1 with an exclusive mount of a disk in aws-us-east-1. JuiceFS Community Edition 1.4.2 with data in Amazon S3 and metadata in ElastiCache for Redis 7.1 in the same Availability Zone, mounted with its defaults (1 s attribute cache, local disk cache) and separately with --writeback. Amazon S3 Files through amazon-efs-utils 3.0.1. Local disk is EBS gp3. Inputs sat on local disk, so GitHub and the npm registry aren't in the times: git clone of the Django repository from a local mirror, and npm ci --prefer-offline --ignore-scripts of a Next.js 15 app (18,602 files) from a warm local cache. Each run is timed until its writes are durable: archil sync on Archil, sync -f elsewhere, and for JuiceFS writeback also until every block staged on local disk had uploaded to S3. Medians of 3 runs. Run it yourself.

npm ci, 18,602 files, until durable

Lower is better
  • Archil12.4 s
  • JuiceFS, writeback mode53.8 s

    Staged on local disk, then uploaded; timed until the upload finished

  • JuiceFS, default mode2 min 42 s
  • Local disk (EBS gp3), for reference10.7 s

git clone Django, until durable

Lower is better
  • Archil19.8 s
  • JuiceFS, writeback mode29.2 s
  • JuiceFS, default mode4 min 7 s
  • Local disk (EBS gp3), for reference15.5 s

How they differ

Architecture

JuiceFS Cloud and Enterprise use Juicedata's own Raft-based metadata engine. Beyond FUSE, JuiceFS offers Hadoop and Python SDKs, a CSI driver, an S3 Gateway and WebDAV.

Archil's managed SSD tier is replicated across Availability Zones. Clients take delegations so creates and writes are acknowledged locally, and disks mount in Kubernetes through the CSI driver.

Data format and your bucket

The biggest difference. JuiceFS's docs say you can't find the original file in object storage; reads go through JuiceFS. Its format is stable across releases.

On an Archil disk synced to your bucket, Spark, Athena or aws s3 keep working on the same objects. Sync is asynchronous; writes are durable on Archil when fsync returns. If you leave, the objects stay.

Consistency and sharing

JuiceFS gives close-to-open consistency, with one-second kernel metadata caches by default.

Archil shared mode gives local-disk speed on checked-out paths; conditional mode lets any client write where no one has checked out. Committed writes are strongly consistent, including over S3.

Snapshots and branching

juicefs clone shares blocks and writes new ones on change; clones can't cross volumes.

An Archil branch can mount on a different machine, one per agent attempt or training run. Branching disks synced to your own bucket is an Enterprise feature; see plan features.

Pricing model

JuiceFS Community Edition is free; you pay for storage and the metadata engine. Cloud bills per GiB-month, Enterprise by volume. See JuiceFS pricing.

Archil bills active data per GiB-month, with a lower archive rate on Archil-managed disks; on synced disks you pay your provider for the bucket. See Archil pricing.

Which one should you use?

Use JuiceFS when

  • you want open source you can run anywhere, including on-premises
  • you need a backend Archil doesn't support, such as HDFS or WebDAV
  • you're happy to run, or choose, a metadata database
  • the data is only read through the file system

Use Archil when

  • S3 tools and pipelines must read the bucket directly
  • you want to mount an existing dataset without copying it
  • you want nothing to operate
  • agents or training runs need whole-disk branches in milliseconds
  • agents need a sandbox next to the data

Questions people ask

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