zpaqfranz
Snappy
zpaqfranz | Snappy | |
---|---|---|
4 | 5 | |
227 | 5,994 | |
- | 0.6% | |
8.7 | 5.2 | |
18 days ago | 19 days ago | |
C++ | C++ | |
MIT License | GNU General Public License v3.0 or later |
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zpaqfranz
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How to ensure file integrity?
Now, onto files backup - if you value your data, don't make just one backup copy, make two or three. Also, I'd recommend using software that will make snapshots and you could restore whichever version you need. I am using zpaqfranz for few years now, it is command line software but you can make batch file and update the archive when needed - it will add only new and changed files, so only first backup will last long.
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Which compression algorithm/file type for backups?
ZPAQ1 is great, it supports incremental backups and compression algorithm is really good even on already compressed data like images. zpaqfranz2 is a fork that adds more advanced checksumming algorithms. It's also worth looking into.
- Zpaqfranz: Advanced and compatible fork of ZPAQ 7.15
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WINRAR - I have 20GB RAR file that I update daily. Issue is, whenever I want to add new file to that archive, it has to update all of those files that are pre-existing, it lasts just as long as it took it to create that 20GB archive. Is there a way to update archive without updating entire archive?
For best results I recommend the compatible fork with the latest advancements: https://github.com/fcorbelli/zpaqfranz
Snappy
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Why I enjoy using the Nim programming language at Reddit.
Another example of Nim being really fast is the supersnappy library. This library benchmarks faster than Google’s C or C++ Snappy implementation.
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Stretch iPhone to Its Limit: 2GiB Stable Diffusion Model Runs Locally on Device
It doesn't destroy performance for the simple reason that nowadays memory access has higher latency than pure compute. If you need to use compute to produce some data to be stored in memory, your overall throughput could very well be faster than without compression.
There have been a large amount of innovation on fast compression in recent years. Traditional compression tools like gzip or xz are geared towards higher compression ratio, but memory compression tends to favor speed. Check out those algorithms:
* lz4: https://lz4.github.io/lz4/
* Google's snappy: https://github.com/google/snappy
* Facebook's zstd in fast mode: http://facebook.github.io/zstd/#benchmarks
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Compression with best ratio and fast decompression
Google released Snappy, which is extremely fast and robust (both at compression and decompression), but it's definitely not nearly as good (in terms of compression ratio). Google mostly uses it for real-time compression, for example of network messages - not for long-term storage.
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How to store item info?
Just compress it! Of course if you will you ZIP, players will able to just open this zip file and change whatever they want. But you can use less popular compression algorithms which are not supported by default Windows File Explorer. Snappy for example.
- What's the best way to compress strings?
What are some alternatives?
borgmatic - Simple, configuration-driven backup software for servers and workstations
zstd - Zstandard - Fast real-time compression algorithm
lepton - Lepton is a tool and file format for losslessly compressing JPEGs by an average of 22%.
LZ4 - Extremely Fast Compression algorithm
Bareos - Bareos is a cross-network Open Source backup solution (licensed under AGPLv3) which preserves, archives, and recovers data from all major operating systems.
brotli - Brotli compression format
dwarfs - A fast high compression read-only file system for Linux, Windows and macOS
ZLib - A massively spiffy yet delicately unobtrusive compression library.
par2cmdline - Official repo for par2cmdline and libpar2
LZMA - (Unofficial) Git mirror of LZMA SDK releases
CryptSync - CryptSync is a small utility that synchronizes two folders while encrypting the contents in one folder. That means one of the two folders has all files unencrypted (the files you work with) and the other folder has all the files encrypted.
zlib-ng - zlib replacement with optimizations for "next generation" systems.