One corpus, many codecs
Every codec compresses the identical bytes. No warmed cache for one and not another, no different file set.
Comparison
Compare us the way
an engineer would.
We publish results against Brotli, Zstandard, gzip, XZ and LZ4 — including the workloads where they win. This page is not a scorecard with our logo on top; it is how to run a comparison that would survive your own review.
A fair comparison
Six rules that make the result mean something.
Compare complete containers
Measure the full emitted frame — headers, metadata and integrity envelope included — not a payload-only figure.
Decode must return the source
A size win only counts if the decode reproduces the original bytes exactly. That is the contract, for every codec.
Speed is hardware-specific
Throughput means nothing without the machine, runtime and settings. Apple M4 Max, 36 GB (macOS arm64) The only baseline that counts is yours.
Name the profiles and levels
Brotli -q11, zstd -19, xz -9 and LZ4 -1 target very different trade-offs. Compare like with like, and say which.
The winning test is your corpus
Published results are direction, not destiny. The decisive comparison is your representative data against your current codec.
Where each one wins
The honest split.
A comparison that only shows our strong side is marketing. These are the categories where we are built to win, and the ones where a standard codec is the better tool.
Where Saar is built to win
- Structured and scientific records where savings compound and recovery must be exact.
- Telemetry, logs and event streams handled as bounded, ordered, checked chunks.
- Archives and cold storage where byte reduction offsets cost and reads are rare.
- Zero-heavy and sparse data, kept only when the sparse candidate verifies smaller.
Where the standard codec wins
- Already-compressed media (PNG, MP4, JPEG, Ogg): no lossless method can shrink them further.
- Ultra-low-latency hot paths that need LZ4-class speed on near-incompressible data.
- Zero-dependency, ubiquitous tooling already in your stack, with no evaluation step.
- A universal win: no codec leads on every workload, including ours.
The only comparison that counts
Your codec, your data, your machine.
A baseline is the workload’s own current codec, measured on your representative environment. Not our development laptop, and not a published table.
Export a representative sample
Real files from the workload you are actually deciding on.
Run both, same machine
Your current codec and Saar, identical input, whole containers, exact recovery.
Decide on the numbers you produced
Keep the result either way — it is your data and your call.
Evidence first
See the reproducible results.
Every study names the corpus, revision, environment, settings and limitations — including where we do not lead.