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Mount (Everest)

lakeFS Cloud

lakeFS Enterprise

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Everest is a complementary binary to lakeFS that allows users to virtually mount a remote lakeFS repository onto a local directory. Once mounted, users can access the data as if it resides on their local filesystem, using any tool, library, or framework that reads from a local filesystem. This functionality is currently in limited support and is a Read-Only file system and is pointing to a commit in lakeFS.

Note ⚠️ Everest is currently in beta. There is no installation required, please contact us to get access to the Everest binary.

Use Cases

  • Simplified Data Loading: With lakeFS Mount, there’s no need to write custom data loaders or use special SDKs. You can use your existing tools to read files directly from the filesystem.
  • Handle Large-scale Data Without changing Work Habits: Seamlessly scale from a few local files to millions without changing your tools or workflow. Use the same code from early experimentation all the way to production.
  • Enhanced Data Loading Efficiency: lakeFS Mount supports billions of files and offers fast data fetching, making it ideal for optimizing GPU utilization and other performance-sensitive tasks.


  • For enterprise installations: lakeFS Version 1.25.0 or higher.

OS and Protocol Support

Currently the implemented protocols are nfs and fuse.

  • NFS V3 (Network File System) is supported on macOS.
  • FUSE is supported on Linux (no root required).

Authentication with lakeFS

The authentication with the target lakeFS server is equal to lakectl CLI. Searching for lakeFS credentials and server endpoint in the following order:

  • Command line flags --lakectl-access-key-id, --lakectl-secret-access-key and --lakectl-server-url
  • LAKECTL_* Environment variables
  • ~/.lakectl.yaml Configuration file or via --lakectl-config flag

Command Line Interface

Mount Command

The mount command is used to mount a lakeFS repository to a local directory, it does it in 2 steps:

  • Step 1: Starting a server that listens on a local address and serves the data from the remote lakeFS repository.
  • Step 2: Running the required mount command on the OS level to connect the server to the local directory.


  • Since the server runs in the background set --log-output /some/file to view the logs in a file.
  • Cache: Everest uses a local cache to store the data and metadata of the lakeFS repository. The optimal cache size is the size of the data you are going to read.
  • Reusing Cache: between restarts of the same mount endpoint, set --cache-dir to make sure the cache is reused.
  • Mounted data consistency: When providing lakeFS URI mount endpoint lakefs://<repo>/<ref>/<path> the <ref> should be a specific commit ID. If a branch/tag is provided, Everest will use the HEAD commit instead.


everest mount <lakefs_uri> <mount_directory>

--presign: Use presign for downloading.
--cache-dir: Directory to cache read files in.
--cache-size: Size of the local cache in bytes.
--cache-create-provided-dir: If cache-dir is explicitly provided and does not exist, create it.
--listen: Address to listen on.
--no-spawn: Do not spawn a new server, assume one is already running.
--protocol: Protocol to use (default: nfs).
--log-level: Set logging level.
--log-format: Set logging output format.
--log-output: Set logging output(s).

Umount Command

The umount command is used to unmount a currently mounted lakeFS repository.

everest umount <data_directory>

mount-server Command (Advanced)

Note ⚠️ The mount-server command is for advanced use cases and will only spin the server without calling OS mount command.

The mount-server command starts a mount server manually. Generally, users would use the mount command which handles server operations automatically.

everest mount-server <remote_mount_uri>
--cache-dir: Directory to cache read files and metadata.
--cache-create-provided-dir: Create the cache directory if it does not exist.
--listen: Address to listen on.
--protocol: Protocol to use (nfs | webdav).
--callback-addr: Callback address to report back to.
--log-level: Set logging level.
--log-format: Set logging output format.
--log-output: Set logging output(s).
--cache-size: Size of the local cache in bytes.
--parallelism: Number of parallel downloads for metadata.
--presign: Use presign for downloading.


Note ⚠️ For simplicity, the examples show main as the ref, Everest will always mount a specific commit ID, given a ref it will use the HEAD (e.g most recent commit).

Data Exploration

Mount the lakeFS repository and explore data as if it’s on the local filesystem.

everest mount "lakefs://image-repo/main/datasets/pets/" "./pets"
ls -l "./pets/dogs/"
find ./pets -name "*.small.jpg"
open -a Preview "./pets/dogs/golden_retrievers/cute.jpg"
everest umount "./pets"

Working with Data Locally

Mount the remote lakeFS server and use all familiar tools without changing the workflow.

everest mount "lakefs://image-repo/main/datasets/pets/" "./pets" --input "./pets"
duckdb "SELECT * FROM read_parquet('pets/labels.parquet')"
everest umount "./pets"


How do I get started with lakeFS Mount (Everest)?

lakeFS Mount is avaialble for lakeFS Cloud and lakeFS Enterprise customers. Once your setup is complete, contact us to access the lakeFS Mounts (beta) binary and follow the provided docs.

  • Want to try lakeFS Cloud? Signup for a 30-day free trial.
  • Interested in lakeFS Enterprise? Contact sales for a 30-day free license.

Can I write to lakeFS using lakeFS Mount?

Currently, lakeFS Mount supports read-only file system operations. Write support is on our roadmap and will be added in the future.

What operating systems are supported by lakeFS Mount?

lakeFS Mount supports Linux and MacOS. Windows support is on the roadmap.

How can I control access to my data when using lakeFS Mount?

You can use lakeFS’s existing Role-Based Access Control mechanism, which includes repository and path-level policies. lakeFS Mount translates filesystem operations into lakeFS API operations and authorizes them based on these policies.

Does data pass through the lakeFS server when using lakeFS Mount?

lakeFS Mount leverages pre-signed URLs to read data directly from the underlying object store, meaning data doesn’t pass through the lakeFS server. By default, presign is enabled. To disable it, use:

everest mount <lakefs_uri> <mount_directory> --presign=false

What happens if a lakeFS branch is updated after I mount it?

lakeFS Mount points to the commit that was the HEAD commit of the branch at the time of mounting. This means the local directory reflects the branch state at the time of mounting and does not update with subsequent branch changes.

When are files downloaded to my local environment?

lakeFS Mount uses a lazy prefetch strategy. Files are not downloaded at mount time or during operations that only inspect file metadata (e.g., ls). Files are downloaded only when commands that require file access (e.g., cat) are used.

When using lakeFS Mount, the volume of data accessed by the local machine influences the scale limitations more than the total size of the dataset under the mounted prefix. This is because lakeFS Mount uses a lazy downloading approach, meaning it only downloads the accessed files. lakeFS Mount listing capability is limited to performing efficiently for prefixes containing fewer than 8000 objects, but we are working to increase this limit.

Ensure your cache size is large enough to accommodate the volume of files being accessed.

How does lakeFS Mount integrate with a Git repository?

It is perfectly safe to mount a lakeFS path within a Git repository. lakeFS Mount prevents git from adding mounted objects to the git repository (i.e when running git add -A) by adding a virtual .gitignore file to the mounted directory.

The .gitignore file will also instruct Git to ignore all files except .everest/source and in its absence, it will try to find a .everest/source file in the destination folder, and read the lakeFS URI from there. Since .everest/source is in source control, it will mount the same lakeFS commit every time!

I’m already using lakectl local for working with lakeFS data locally, why should I use lakeFS Mount?

While both lakectl local and lakeFS Mount enable working with lakeFS data locally, they serve different purposes:

Use lakectl local
Use lakeFS Mount

For read-only local data access. lakeFS Mount offers several benefits over lakectl local:

  • Optimized selective data access: The lazy prefetch strategy saves storage space and reduces latency by only fetching the required data.
  • Reduced initial latency: Start working on your data immediately without waiting for downloads.

Note Note: Write support for lakeFS Mount is on our roadmap.