How To Increase File Transfer Speed Using Parallel Rsync?

Remote sync or rsync is a powerful tool primarily used for efficiently transferring and synchronizing files across systems while minimizing data transfer by only copying the differences between source files and the existing files in the destination. This makes it exceptionally useful for backups and maintaining identical copies of files in different locations.

Rsync can operate both locally and over a network or can use its own native protocol if it's operating in daemon mode. It includes many options to control its behavior and output, making it a very flexible tool suitable for a variety of file transfer tasks. In this article, you'll learn about file transfer speed using parallel rsync.

Apply the Right Method to Increase File Transfer Speed

To increase file transfer speeds using parallel Rsync, you can employ several methods to run multiple rsync processes simultaneously, efficiently managing large datasets and numerous files across different servers. Here's a concise overview of the primary techniques:

GNU Parallel

GNU Parallel is a versatile shell tool designed to optimize the execution of jobs like rsync tasks across one or multiple computers.

By splitting input lists, such as files or URLs, into smaller segments, GNU Parallel can pipe these segments into several rsync commands running concurrently. This parallel execution allows for multiple data transfers to happen at the same time, significantly reducing the total time required for synchronization.

The tool intelligently balances the workload across available processors, enhances resource utilization, and simplifies output and error management. This approach is particularly effective in environments with large datasets, where efficient data synchronization is critical. Through its ability to manage parallel rsync operations, GNU Parallel provides a substantial boost in performance and operational efficiency.

Multi-Stream Rsync

Msrsync is a wrapper for rsync designed to improve data transfer speeds, especially over local area networks (LANs), by parallelizing tasks. It works by splitting a single data transfer job into multiple streams or threads, allowing several parts of the data to be synchronized simultaneously. This parallelization maximizes bandwidth utilization, fully exploiting the network capacity to accelerate transfer rates.

Traditional rsync operations, which process data sequentially, are outpaced by Msrsync as it divides the workload into several concurrent streams, significantly cutting down synchronization time. Users can adjust the number of streams to optimize performance based on their specific network conditions and data volumes.

Msrsync retains compatibility with standard rsync commands, making it easy to integrate into current setups without needing extensive changes. This makes Msrsync particularly useful for large data backups, mirroring, and scenarios where quick data transfer is essential.


Parasyncfp is a Perl script that enhances rsync by implementing parallel threading, making it ideal for transferring large datasets over fast networks.

It orchestrates multiple rsync processes to run concurrently, effectively utilizing available network bandwidth to expedite data synchronization. This parallel processing capability significantly improves the speed and efficiency of data transfers, especially in environments like data centers where quick, large-volume data movements are essential.

Additionally, Parasyncfp features bandwidth throttling to prevent network overload, ensuring that parallel transfers do not monopolize network resources. This makes it a particularly useful tool for operations such as backups, disaster recovery, and data mirroring.

The script is scalable, allowing users to adjust the number of parallel processes based on their specific requirements and network conditions. Despite its advanced functionality, Parasyncfp maintains compatibility with standard rsync commands, facilitating easy integration into existing workflows and systems.

Launching Multiple Rsync Sessions

Manually initiating multiple rsync sessions to run at the same time can also achieve parallel synchronization. This approach involves segmenting the dataset into smaller parts and using separate rsync commands to handle different segments concurrently. It requires more setup but offers flexibility and can be customized to specific synchronization needs.

Consider P2P Replication to Increase File Transfer Speed

P2P replication architecture, like Resilio enables every device in your network to both distribute and receive data. This system supports bidirectional syncing for any file size or quantity across numerous endpoints. Its WAN optimization technology ensures reliable syncing across networks prone to latency or data loss.

Choose a P2P replication solution that is highly reliable, with no single point of failure, ensuring timely and accurate data delivery. It allows rapid file synchronization across global servers in any direction, making network expansion straightforward by simply adding more servers. A user-friendly system allows automation through scripts, APIs, or directly within the user interface. Moreover, pick a solution supported by top-tier engineering, freeing you from script management and maintenance.

Schedules are predictable, crucial for coordinating large-scale synchronizations across multiple servers for various operations. The system operates transparently—users manage files as usual without additional steps and easily integrate with existing applications via an API. Security features include end-to-end AES-256-bit encryption and cryptographic data integrity checks.


Each of the methods above leverages the concept of parallel processing to boost the performance of rsync, a tool originally designed for simpler, smaller-scale tasks. By running multiple instances of rsync simultaneously, whether through scripts, specialized wrappers, or parallel execution tools, you can reduce the time it takes to synchronize large volumes of data across multiple locations.

Jay Bats

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