zopfli

Pros of Brotli

• Better compression ratio, especially for small files
• Faster decompression speed
• Wider browser support and adoption in web standards

Cons of Brotli

• Slower compression speed, especially at higher compression levels
• More complex implementation, requiring more development resources

Code Comparison

Zopfli (C):

size_t ZopfliCompress(const ZopfliOptions* options,
                      ZopfliFormat output_type,
                      const unsigned char* in,
                      size_t insize,
                      unsigned char** out,
                      size_t* outsize);

Brotli (C):

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

Both libraries offer compression functionality, but Brotli provides more fine-grained control over compression parameters. Zopfli focuses on achieving the smallest possible output size, while Brotli balances compression ratio with speed and offers different modes for various use cases.

Brotli has gained more traction in web development due to its superior compression and decompression performance, making it a preferred choice for modern web applications. However, Zopfli remains useful for offline compression tasks where compression time is less critical.

Pros of zlib

• Faster compression and decompression speeds
• Widely adopted and supported across many platforms and programming languages
• Smaller memory footprint during compression/decompression operations

Cons of zlib

• Generally achieves lower compression ratios compared to Zopfli
• Less optimized for scenarios where compression time is not a critical factor

Code Comparison

zlib (compression example):

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

Zopfli (compression example):

ZopfliOptions options;
ZopfliInitOptions(&options);
unsigned char* out = 0;
size_t outsize = 0;
ZopfliCompress(&options, ZopfliFormat, in, insize, &out, &outsize);

Both libraries offer compression functionality, but Zopfli focuses on achieving higher compression ratios at the cost of slower compression speed. zlib provides a more balanced approach with faster compression and decompression, making it suitable for real-time applications. Zopfli is often used for static content where compression time is less critical. zlib's widespread adoption and cross-platform support make it a popular choice for many developers, while Zopfli is typically used in specific scenarios where maximum compression is desired.

Pros of Zstd

• Significantly faster compression and decompression speeds
• Better compression ratios at higher levels
• Supports dictionary compression for improved efficiency

Cons of Zstd

• Slightly larger compressed file sizes at lower compression levels
• More complex implementation, potentially harder to integrate

Code Comparison

Zopfli (C):

size_t c_size = 0;
unsigned char* compressed = compress(input, input_size, &c_size);

Zstd (C):

size_t c_size = ZSTD_compressBound(input_size);
void* compressed = malloc(c_size);
c_size = ZSTD_compress(compressed, c_size, input, input_size, 1);

Both libraries offer compression functionality, but Zstd provides more options and control over the compression process. Zstd's API is more extensive, allowing for advanced features like dictionary compression and adjustable compression levels.

Zopfli focuses on producing smaller compressed files at the cost of slower compression speed, making it suitable for scenarios where compression time is not critical. Zstd, on the other hand, prioritizes speed while maintaining good compression ratios, making it more versatile for real-time applications and scenarios where both speed and compression efficiency are important.

Pros of lz4

• Extremely fast compression and decompression speeds
• Suitable for real-time applications and scenarios requiring low latency
• Widely adopted and supported across various platforms and programming languages

Cons of lz4

• Lower compression ratio compared to Zopfli
• Not optimized for maximum compression, prioritizing speed instead

Code Comparison

lz4:

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

Zopfli:

unsigned char* out = 0;
size_t outsize = 0;
ZopfliCompress(&options, ZopfliFormat, in, insize, &out, &outsize);

Key Differences

• lz4 focuses on speed and efficiency, making it ideal for scenarios where quick compression/decompression is crucial
• Zopfli prioritizes achieving the highest possible compression ratio, sacrificing speed for better compression
• lz4 is more versatile and widely used in various applications, while Zopfli is primarily used for static content where compression time is not a concern
• lz4 offers both compression and decompression functionality, whereas Zopfli is mainly used for compression, relying on existing zlib-compatible decompressors

Pros of miniz

• Faster compression and decompression speeds
• Simpler API and easier integration into existing projects
• Supports both zlib and deflate compression formats

Cons of miniz

• Generally achieves lower compression ratios compared to Zopfli
• Less optimized for producing the smallest possible output size
• May not be suitable for scenarios where file size is the top priority

Code comparison

miniz:

mz_uint32 cmp_status;
uLong cmp_len = compressBound(src_len);
cmp_status = compress(pDst, &cmp_len, pSrc, src_len);

Zopfli:

ZopfliOptions options;
ZopfliInitOptions(&options);
ZopfliCompress(&options, ZopfliFormat::ZOPFLI_FORMAT_DEFLATE,
               src, src_len, &out, &outsize);

Summary

miniz is a lightweight, fast, and easy-to-use compression library that supports both zlib and deflate formats. It offers better speed and simpler integration but may not achieve the same level of compression as Zopfli. Zopfli, on the other hand, focuses on producing the smallest possible output size at the cost of slower compression speed. The choice between the two depends on whether speed or file size is the primary concern for the specific use case.