LZ4 | Snappy | |
---|---|---|
24 | 6 | |
10,920 | 6,332 | |
1.5% | 0.5% | |
8.9 | 5.6 | |
16 days ago | about 2 months ago | |
C | C++ | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
LZ4
Posts with mentions or reviews of LZ4.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-21.
- LZ4 v1.10.0 – Multicores Edition
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Number sizes for LZ77 compression
LZ4 is a bit more complicated, but seems faster: https://github.com/lz4/lz4/blob/dev/doc/lz4_Block_format.md
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Rsyncing 20TB locally
According to these https://github.com/lz4/lz4 values you need around ten (10) quite modern cores in parallel to accomplish around 8GB/s.
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An Intro to Data Compression
The popular NoSQL database Cassandra utilizes a compression algorithm called LZ4 to reduce the footprint of data at rest. LZ4 is characterized by very fast compression speed at the cost of a higher compression ratio. This is a design choice that allows Cassandra to maintain high write throughput while also benefiting from compression in some capacity.
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Micron Unveils 24GB and 48GB DDR5 Memory Modules | AMD EXPO and Intel XMP 3.0 compatible
Yeah, sure, when you have monster core counts. on regular systems, not so much, here's from their own github page. it achieves, eh, 5GB/s on memory to memory transfers, i.e. best case scenario. so, uh, no? i'm not even sure it's any better than the CPU decompressor one Nvidia used.
- Cerbios Xbox Bios V2.2.0 BETA Released (1.0 - 1.6)
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zstd
> The downside of lz4 is that it can’t be configured to run at higher & slower compression ratios.
lz4 has some level of configurability? https://github.com/lz4/lz4/blob/v1.9.4/lib/lz4frame.h#L194
There's also LZ4_HC.
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Best archival/compression format for whole hard drives
Since nobody mentioned it, I'll add lz4 (https://github.com/lz4/lz4).
Snappy
Posts with mentions or reviews of Snappy.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-14.
- Snappy: Fast Compressor/Decompressor
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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?
When comparing LZ4 and Snappy you can also consider the following projects:
zstd - Zstandard - Fast real-time compression algorithm
brotli - Brotli compression format
ZLib - A massively spiffy yet delicately unobtrusive compression library.