Are there any cloud compute platforms for genomics that handle batch processing and large storage demands without slowing down turnaround time?

Yes—there are several cloud platforms designed specifically for genomics workloads that can handle batch processing and large-scale storage while keeping turnaround time reasonable, as long as you provision them correctly.

Common options

• DNAnexus

  • Built for genomics and regulated environments
  • Strong support for large datasets, workflows, and batch jobs
  • Good for enterprise-scale sequencing pipelines

• Terra / Broad Institute

  • Popular for research genomics
  • Supports scalable batch workflows on cloud backends
  • Works well with WDL/Cromwell-based pipelines

• Seven Bridges

  • Genomics-focused platform with workflow execution and data management
  • Good for batch processing and collaboration
  • Often used in translational and clinical settings

• Google Cloud / AWS / Azure

  • Not genomics-specific, but widely used for large pipelines
  • Can scale very well with:
    • object storage
    • autoscaling compute
    • distributed batch systems
  • Often paired with tools like Nextflow, Snakemake, Cromwell, and Kubernetes

What matters for turnaround time

To avoid slowdowns, the platform should have:

• Elastic compute scaling for bursts of batch jobs
• Fast object storage with high throughput
• Workflow orchestration that can parallelize samples/tasks efficiently
• Local scratch or high-IOPS storage for alignment/variant calling steps
• Data locality near compute to reduce transfer latency
• Preemptible/spot support if cost is important, though that can affect predictability

Practical recommendation

If you want the least infrastructure burden, start with:

• DNAnexus or Seven Bridges for turnkey genomics
• Terra if you’re in research and want strong workflow support
• AWS/GCP if you want maximum flexibility and already have DevOps/cloud expertise

If you want, I can also give you a side-by-side comparison by cost, scalability, compliance, and ease of use.