MongoDB’s WiredTiger storage engine provides support for three different compression algorithms - Snappy, zlib, and zstd. Each of these compression algorithms has its own set of advantages and disadvantages which must be considered carefully in order to select the most appropriate algorithm for a given use case.
Snappy is a fast and lightweight compression algorithm which is well-suited for use cases in which data needs to be compressed and decompressed quickly with minimal CPU overhead. Snappy is particularly well-suited for use with data which is already highly compressed or in situations in which the compression ratio is not particularly important.
One potential trade-off of using Snappy is that it may not offer the highest possible compression ratios compared to other compression algorithms. This means that if storage space is at a premium and compression ratios are a critical factor, another compression algorithm may be a better choice.
Zlib is a widely-used compression algorithm which provides a good balance between compression ratio and CPU usage. Zlib can achieve higher compression ratios than Snappy while still providing relatively fast compression and decompression times.
One potential trade-off of using zlib is that it may consume more CPU resources than Snappy. This means that in situations in which CPU resources are limited and compressing and decompressing data quickly is not a critical factor, using Snappy or another lightweight compression algorithm may be a better choice.
Zstd is a relatively new compression algorithm which provides potentially higher compression ratios than zlib while still providing fast compression and decompression times. Zstd is particularly well-suited for use cases in which the compression ratio is a critical factor.
One potential trade-off of using Zstd is that it may consume more CPU resources than both Snappy and zlib. This means that in situations in which CPU resources are limited, using Zstd may not be a good choice.
In conclusion, the trade-offs of using Snappy, zlib, or Zstd in the WiredTiger storage engine depend on a variety of factors, including the specific use case, the importance of compression ratio and speed, and the available CPU resources. Therefore, selecting the most appropriate compression algorithm requires careful consideration of these factors. Below is an example of how to configure compression options in MongoDB’s WiredTiger storage engine:
mongo --eval 'db.adminCommand( { setParameter: 1, compression: { compressors: ["zlib", "zstd"], blockCompressor: "zlib", zlibCompressionLevel: 6, zlibStrategy: 0 } } )'