This comparison table is taken from the book “Architecture and Design of the Linux Storage Stack” which I find useful to help understand the differences between the two.
Journaling
Copy-On-Write
Write handling
Changes are recorded in a journal before applying them to the actual file system
A separate copy of data is created to make modifications
Original data
Original data gets overwritten
Original data remains intact
Data Consistency
Ensures consistency by recording metadata changes and replaying them if needed
Ensures consistency by never modifying the original data
Performance
Minimal overhead depending on the type of journaling mode
Some performance gains because of faster writes
Space utilisation
Journal size is typically in MB, so no additional space is required
More space is required due to separate copies of data
Recovery times
Fast recovery times as the journal can be replaced instantly
Slower recovery times as data needs to be reconstructed using recent copies
Features
No built-in support for features such as compression or deduplication
Built-in support for compression and deduplication
Taken from “Architecture and Design of the Linux Storage Stack”
Copy-On-Write Filesystem does not overwrite the data in place, here is how it is done. Supposedly there is file that will be modified.
Copy the old data to an allocated location on the disk
New data is written to the allocated location on the disk.
Hence the name Copy-and-Write
The references for the new data are updated
However, the old data and its snapshots are still there
As described in the Architecture and Design of Linux Storage Stack by Muhammad Umer Page 59
As the old data is preserved in the process, filesystem recovery is very simplified. Since the previous state of the data is saved on another allocated location on disk. If there is an outrage, the system system can easily revert to its former state. This make the maintenance of any Journal obsolete. This also allows snapshots to be implemented at the filesystem level.
As the old data is still there, space utilisation may be more than what the user expects……
Some of the filesystem the use the CoW based approach includes Zttabyte Filesystem (ZFS) and B-Tree Filesystem (Btrfs)
The journaling file system (JFS) is a kind of file system developed by IBM IN 1990. It keeps track of changes, which are not yet committed to the file system’s main part, by recording the goal of such changes in a data structure known as “journal”. Usually, the “journal” is a circular log.
In the event of a system crash or power failure, a journaling file system can be brought back online more quickly with a lower chance of being corrupted. Depending on the actual implementation, the JFS may only keep track of stored metadata, which results in improved performance at the expense of increased possibility for data corruption.
Here is a diagram taken from Architecture and Design of Linux Storage Stack by Muhammad Umer Page 57
According to the Chapter 3 of the book,
From the diagram, any changes made to the filesystem are written sequentially to a journal, also called a transaction. Once a transaction is written to a journal, it is written to an appropriate location on a disk. In the case of a system crash, the filesystem replays the journal to see whether any transaction is incomplete. When the transaction has been written to its on-disk location, it is removed from the Journal.
It is interesting to note that either the metadata or actual data is first written to the data. Either way, once written to the filesystem, the transaction is removed from the journal. The size of the journal can be a few megabytes.
Benefits of Journal File System and Impact on Performance
Besides making the Filesystem more reliable and preserving its structure in system crashes and hardware failures, the burning question is whether it will impact performance?
Generally, journaling improves performance when it is enabled by having fewer seeks to the physical disks as data is only when a journal is committed or when the journal fills up. For example, in intense meta-data operations like recursive operations on the directory and its content, journaling improves performance by reducing frequent trips to disks and performing multiple updates as a single unit of work.
The Linux kernel supports many filesystems that are native to Linux, but there are other filesystem that Linux support via FileSystem in USErspace (FUSE). Probably you would guess one prominent example of a Filesystem outside Linux that Linux user face often – Windows NTFS
I have written an entire blog on how to get your portable drive on NTFS working. For more information, do take a look at Mounting NTFS on Rocky Linux 8
Another popular usage of FUSE driver is sshfs. It is using SSH to mount the remote file system and avoid the need to setup up NFS or SAMBA while enjoying the benefits of SSH encryption.
If you are planning to mount like a portable drive using Windows NTFS File System on the Rocky Linux 8, what you will see immediately when you issue the command after you plug the portable drive in
# mount /dev/sdd1 /data1
mount: /data1: unknown filesystem type 'ntfs'.
Step 1: Enable EPEL Repo
# dnf install epel-release
Step 2: Install NTFS-3g
# dnf install ntfs-3g
In some blogs written elsewhere, these 2 packages are more than enough, but I was still having issues. In my situation, I need to put in 5 packages
TMPFS is a filesystem that exists only in memory. When you reboot the Server, the content of the TMPFS is gone. This is perfect for mounting the /tmp directory
In your /etc/fstab
tmpfs /tmp tmpfs size=30% 0 0
The size option set the maximum size of the filesystem. In the setting above, it can take up to 30% of the total RAM. If you umount the file system, all memory is returned.
This IBM® Redpaper publication describes support for Red Hat OpenShift Container Platform application data protection with IBM Spectrum® Protect Plus. It explains backup and restore operations for persistent volume data by using the Container Storage Interface (CSI) plug-in.
Table of Contents
Chapter 1. Introducing containers Chapter 2. IBM Spectrum Protect Plus architecture Chapter 3. Installing IBM Spectrum Protect Plus as a containerized application Chapter 4. Container Backup Support Chapter 5. Implementing Container Backup Support Chapter 6. Using Container Backup Support Chapter 7. Red Hat OpenShift cluster disaster recovery solution
IBM Spectrum Scale Container Native Storage Access (CNSA) allows the deployment of Spectrum Scale in a Red Hat OpenShift cluster. Using a remote mount attached file system, CNSA provides a persistent data store to be accessed by the applications via the IBM Spectrum Scale Container Storage Interface (CSI) driver using Persistent Volumes (PVs).