![]() Connect uses a P2P (peer-to-peer) transfer architecture and WAN optimization to easily replicate files of any size or number over any network. Resilio Connect is a server replication solution that can handle the synchronization, distribution, and consolidation tasks that Rsync (and other solutions) can’t. As your replication environment grows (i.e., replicating large files, replicating larger numbers of files, and replicating to many endpoints), you’ll need to find a better file replication solution that can handle your needs. We’ll share several in this article and link to forums where you can find more answers.īut ultimately, you may need to confront the primary issue with Rsync: It’s an aging technology that was built in and designed for a time when files were smaller and replication jobs were small and simple. There are a few solutions you can try to increase sync speed for a large number of files. Rsync can only sync files in one direction. In these scenarios, Rsync’s performance falters due to its rudimentary technology, how it detects file changes, and how it transfers files. However, it’s not a great solution for synchronizing large files or larger file systems containing 100K+ files, complex synchronization scenarios requiring multi-directional sync, and transfer over WANs (wide area networks) or unreliable networks with long retransmission times and varying degrees of packet loss. Rsync works best when network conditions are good (i.e., low-latency and minimal packet loss) and when performing simple replication jobs, such as syncing small files between two offices, distributing a small number files from one endpoint to one or several other endpoints, or consolidating data from one or several endpoints into a single endpoint. A quick Google search for “Rsync large number of files” will return multitudes of forums and articles from Rsync users who are having trouble replicating their large file directories in an acceptable time frame. ![]() Rsync is an open-source, command-line file replication solution that can be extremely slow when replicating a large amount of data. ![]()
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