brotli

Pros of Zstd

• Generally faster compression and decompression speeds
• Better compression ratios at higher levels
• More flexible with adjustable dictionary sizes

Cons of Zstd

• Slightly larger compressed file sizes at lower compression levels
• Less widespread adoption in some ecosystems

Code Comparison

Brotli:

size_t BrotliEncoderCompress(int quality, int lgwin, BrotliEncoderMode mode,
                             size_t input_size, const uint8_t* input_buffer,
                             size_t* encoded_size, uint8_t* encoded_buffer);

Zstd:

size_t ZSTD_compress(void* dst, size_t dstCapacity,
                     const void* src, size_t srcSize,
                     int compressionLevel);

Both libraries offer simple compression functions, but Zstd's API is slightly more straightforward. Brotli provides more fine-grained control over compression parameters in its main function.

Zstd offers a wider range of compression levels (1-22) compared to Brotli (0-11), allowing for more flexibility in balancing compression ratio and speed.

Both projects are actively maintained and have strong community support. Zstd has seen rapid adoption in various applications due to its performance advantages, while Brotli has become a standard in web compression.

Pros of lz4

• Extremely fast compression and decompression speeds
• Low memory usage during compression/decompression
• Suitable for real-time applications and scenarios requiring quick processing

Cons of lz4

• Lower compression ratio compared to Brotli
• Less effective for compressing text-based data
• Not as widely supported in web browsers for content encoding

Code Comparison

lz4

char* compressed = LZ4_compress_default(src, dst, srcSize, dstCapacity);
int decompressedSize = LZ4_decompress_safe(compressed, decompressed, compressedSize, maxDecompressedSize);

Brotli

size_t encoded_size = BrotliEncoderMaxCompressedSize(input_size);
uint8_t* encoded = malloc(encoded_size);
BrotliEncoderCompress(quality, BROTLI_DEFAULT_WINDOW, BROTLI_DEFAULT_MODE, input_size, input, &encoded_size, encoded);

Summary

lz4 excels in speed and efficiency, making it ideal for scenarios where rapid compression/decompression is crucial. However, Brotli generally achieves better compression ratios, especially for text-based data, and has broader support in web environments. The choice between the two depends on the specific use case, with lz4 being preferable for real-time applications and Brotli for optimizing file sizes and web content delivery.

Pros of zlib

• Widely adopted and supported across many platforms and programming languages
• Faster compression and decompression speeds for small to medium-sized files
• Smaller memory footprint during compression and decompression operations

Cons of zlib

• Generally achieves lower compression ratios compared to Brotli
• Less effective for compressing larger files or datasets
• Older algorithm with fewer modern optimizations

Code Comparison

zlib compression example:

z_stream strm;
deflateInit(&strm, Z_DEFAULT_COMPRESSION);
deflate(&strm, Z_FINISH);
deflateEnd(&strm);

Brotli compression example:

BrotliEncoderState* state = BrotliEncoderCreateInstance(NULL, NULL, NULL);
BrotliEncoderCompressStream(state, BROTLI_OPERATION_FINISH, &available_in, &next_in, &available_out, &next_out, &total_out);
BrotliEncoderDestroyInstance(state);

Both libraries offer simple APIs for compression and decompression, but Brotli's API is more modern and provides finer control over compression parameters. zlib's API is more straightforward and requires less setup, which can be beneficial for simpler use cases.

Pros of Snappy

• Faster compression and decompression speeds
• Lower memory usage during compression
• Simpler implementation, easier to integrate into projects

Cons of Snappy

• Lower compression ratio compared to Brotli
• Less suitable for compressing smaller files
• Not as widely supported in web browsers and servers

Code Comparison

Snappy:

char* output = new char[snappy::MaxCompressedLength(input_length)];
size_t output_length;
snappy::RawCompress(input, input_length, output, &output_length);

Brotli:

size_t output_length = BrotliEncoderMaxCompressedSize(input_length);
uint8_t* output = new uint8_t[output_length];
BROTLI_BOOL result = BrotliEncoderCompress(
    BROTLI_DEFAULT_QUALITY, BROTLI_DEFAULT_WINDOW, BROTLI_DEFAULT_MODE,
    input_length, input, &output_length, output);

Snappy focuses on speed and simplicity, making it ideal for scenarios where compression and decompression need to be performed quickly, such as in-memory data compression or real-time data transfer. Brotli, on the other hand, offers better compression ratios at the cost of slower compression speeds, making it more suitable for static content compression and scenarios where file size reduction is prioritized over speed.

Pros of Zopfli

• Achieves higher compression ratios for static content
• Compatible with existing DEFLATE decoders
• Useful for compressing rarely-changed assets

Cons of Zopfli

• Significantly slower compression speed
• Not suitable for real-time compression scenarios
• Limited to DEFLATE-based formats (gzip, PNG)

Code Comparison

Zopfli:

size_t c_size = 0;
unsigned char* compressed = NULL;
ZopfliCompress(&options, ZopfliFormat::ZOPFLI_FORMAT_GZIP,
               input, input_size, &compressed, &c_size);

Brotli:

size_t encoded_size = BrotliEncoderMaxCompressedSize(input_size);
uint8_t* encoded = malloc(encoded_size);
BrotliEncoderCompress(quality, BROTLI_DEFAULT_WINDOW, 
                      BROTLI_DEFAULT_MODE, input_size, input, 
                      &encoded_size, encoded);

Zopfli focuses on achieving maximum compression ratios for static content, making it ideal for compressing assets that don't change frequently. It's compatible with existing DEFLATE decoders, ensuring broad compatibility. However, Zopfli's compression speed is much slower compared to Brotli, making it unsuitable for real-time compression scenarios.

Brotli, on the other hand, offers a better balance between compression ratio and speed. It introduces a new compression format, which requires specific decoder support but achieves better compression ratios than gzip in most cases while maintaining reasonable compression speeds.

Pros of compress

• Supports multiple compression algorithms (Zstandard, LZ4, Snappy) in addition to gzip and deflate
• Generally faster compression and decompression speeds for most use cases
• More actively maintained with frequent updates and improvements

Cons of compress

• Slightly larger compressed file sizes compared to Brotli in some scenarios
• Less widespread adoption and browser support compared to Brotli
• May require additional configuration to achieve optimal compression ratios

Code Comparison

compress:

compressed := bytes.Buffer{}
w := zstd.NewWriter(&compressed)
w.Write(data)
w.Close()

Brotli:

compressed := bytes.Buffer{}
w := brotli.NewWriter(&compressed)
w.Write(data)
w.Close()

Both libraries offer similar ease of use for basic compression tasks. The main difference lies in the specific compression algorithms and their performance characteristics.