Log Compression Calculator

Calculate compressed log storage size and cost savings from a raw log volume and expected compression ratio.

Inputs

Raw Log VolumeGB

Uncompressed log volume over the period being analyzed.

Compression Ratio%

Percent size reduction achieved by compression (e.g. gzip on text logs commonly reaches 80-90%).

Storage Cost$/GB/month

Storage cost per GB per month for your backend (e.g. S3 Standard).

Compressed Size

75.00GB

Storage Savings

425.00GB

Monthly Cost Savings

$9.78

Annual Cost Savings

$117.30

Step by step

Compressed size: raw × (1 − ratio)
500 × (1 − 85/100)
= 75.00 GB
Savings: raw − compressed
500 − 75.00
= 425.00 GB
Monthly cost savings
(500 − 75.00) × $0.023
= $9.78

How it works

Compressing logs before long-term storage shrinks both disk footprint and cost: compressed = raw × (1 − compression_ratio), with savings = raw − compressed. Text-based logs compress especially well because of repetitive structure (timestamps, field names, common log levels), often reaching 80-90% size reduction with standard codecs like gzip or zstd.

Formula

compressed_GB = raw_volume_GB × (1 - compression_ratio_percent / 100)

raw_volume_GB: Uncompressed log volume (GB)
compression_ratio_percent: Percent size reduction achieved by compression

Frequently Asked Questions

What compression ratio should I expect for logs?

Plain text and JSON logs typically compress 80-90% with gzip due to high repetition (field names, timestamps, common values); already-compressed or binary payloads embedded in logs will compress far less.

Does compression affect log search performance?

Yes — compressed logs generally must be decompressed before searching unless your storage/search engine supports compressed-block scanning, so there's a tradeoff between storage savings and query latency for cold/archived data.

Should I compress logs before or after shipping?

Compressing before shipping (e.g. gzip at the agent) reduces network bandwidth too, not just storage — many log shippers support this natively (e.g. Fluent Bit's gzip output compression).

Is zstd better than gzip for logs?

zstd generally offers a better compression-speed tradeoff than gzip at similar or better ratios, and is increasingly the default choice for high-throughput log pipelines that need to compress in real time.

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