Compress
High-density lossless compression for highly structured scientific datasets.
ZCaps for genomics
Compress massive genomic datasets without giving up selective access.
ZCaps brings adaptive lossless compression and chunk-addressable retrieval to large scientific datasets such as VCF, SAM, FASTQ, FASTA, GTF, GFF3 and related bioinformatics workloads.
SCIENTIFIC ARCHIVE98.90 GiB example
Integration maps the selected region to a byte range ↓
Targeted 4 MiB extraction
Target the region. Decode the required chunks. Keep the rest compressed.
Lossless compression for genomic workflows
Access
Retrieve targeted byte ranges by decoding only the relevant compressed chunks.
Scale
Independent chunks and files can be processed concurrently across server resources.
ZCaps addresses bytes and ranges. Chromosome or genomic-coordinate lookup requires an integration layer that maps those coordinates to byte ranges.
01 / Separate genomics benchmark campaign
Large datasets. Measured results.
Selected ZCaps results from the historical genomics campaign. These measurements use a different system and build from the current ZMDC benchmark.
VCF chr21
1000 Genomes phase 3
134.6:1 at level 12
Compare levels 1, 6 and 12
Level 1
- Compression ratio
- 119.5:1
- Compression
- 1,958 MiB/s
- 4 MiB extraction
- 0.11 s
Level 6
- Compression ratio
- 117.6:1
- Compression
- 1,876 MiB/s
- 4 MiB extraction
- 0.11 s
Level 12
- Compression ratio
- 134.6:1
- Compression
- 1,488 MiB/s
- 4 MiB extraction
- 0.16–0.17 s
GTF
Gene annotation
73.07:1 at level 12
Compare levels 1, 6 and 12
Level 1
- Compression ratio
- 38.36:1
- Compression
- 1,498 MiB/s
- 4 MiB extraction
- 0.15–0.16 s
Level 6
- Compression ratio
- 55.76:1
- Compression
- 1,544 MiB/s
- 4 MiB extraction
- 0.16–0.18 s
Level 12
- Compression ratio
- 73.07:1
- Compression
- 997 MiB/s
- 4 MiB extraction
- 0.22–0.25 s
SAM
Sequence alignment
7.92:1 at level 12
Compare levels 1, 6 and 12
Level 1
- Compression ratio
- 5.79:1
- Compression
- 959 MiB/s
- 4 MiB extraction
- 0.27–0.29 s
Level 6
- Compression ratio
- 6.79:1
- Compression
- 808 MiB/s
- 4 MiB extraction
- 0.28–0.33 s
Level 12
- Compression ratio
- 7.92:1
- Compression
- 594 MiB/s
- 4 MiB extraction
- 0.42–0.46 s
FASTQ
Sequencing reads
4.48:1 at level 12
Compare levels 1, 6 and 12
Level 1
- Compression ratio
- 3.87:1
- Compression
- 807 MiB/s
- 4 MiB extraction
- 0.35–0.37 s
Level 6
- Compression ratio
- 4.20:1
- Compression
- 697 MiB/s
- 4 MiB extraction
- 0.39–0.42 s
Level 12
- Compression ratio
- 4.48:1
- Compression
- 493 MiB/s
- 4 MiB extraction
- 0.63–0.67 s
GOA UniProt GAF
Functional annotation
18.63:1 at level 12
Compare levels 1, 6 and 12
Level 1
- Compression ratio
- 12.92:1
- Compression
- 1,164 MiB/s
- 4 MiB extraction
- 0.302–0.315 s
Level 6
- Compression ratio
- 16.25:1
- Compression
- 1,041 MiB/s
- 4 MiB extraction
- 0.301–0.338 s
Level 12
- Compression ratio
- 18.63:1
- Compression
- 715 MiB/s
- 4 MiB extraction
- 0.437–0.488 s
0.11–0.75 smeasured targeted extraction envelope
30 formats · 3 compression levels · 90 compression runs · 270 targeted 4 MiB extraction runs · datasets up to 98.90 GiB.
SHA-256 validation of extracted ranges.
Benchmark system
Intel Core i9-13980HX
16 GiB RAM · NVMe SSD
Windows 11
Historical genomics campaign. Separate from the current ZMDC benchmark. Results are specific to the tested data, build and hardware.
Explore ZCaps technical evidence02 / Scientific data compression
Different structures. Adaptive compression.
Maximum measured compression ratio · ZCaps level 12
0140 ×
ZCaps across different datasets. This chart is not a comparison against competing compressors.
03 / Selective access at scale
Access the part you need.
Observed targeted extraction remained sub-second across the tested size range.
GFF31.65 GiB
JSON6.09 GiB
VCF11.23 GiB
VCF23.50 GiB
Pfam38.71 GiB
FASTA64.20 GiB
GOA GPA71.88 GiB
GOA GAF98.90 GiB
0.11–0.75 sObserved campaign envelope · targeted 4 MiB extraction
File sizes shown are documented examples. The extraction envelope describes the campaign, not individual latency values for each file or a universal latency guarantee.
04 / Bioinformatics infrastructure
One layer for scientific data workflows.
Genomic archives
Retain byte-exact scientific records with lossless bioinformatics compression and selective retrieval.
Variant datasets
Explore VCF compression for large variant collections while retaining targeted byte-range access.
Sequencing pipelines
Integrate FASTQ compression and SAM compression into workflows for reads and alignments.
Research repositories
Reduce repository storage while preserving original files for reproducible research.
Large annotation datasets
Compress GTF, GFF3 and functional annotation records using a data-adaptive engine.
Local scientific infrastructure
Keep compression and genomic random access inside infrastructure controlled by your organization.
High-volume bioinformatics storage
Use scientific data compression across large collections, processing independent files concurrently.
Discuss your workload