Astronomer
Managed Apache Airflow service for orchestrating and monitoring data pipelines in the cloud
Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Scalable, portable, reproducible pipelines powered by dataflow programming
Nextflow lets you build and run data‑driven computational pipelines that scale from a laptop to cloud and HPC, with seamless dependency management via Docker, Conda, Singularity, and more.
Nextflow is a workflow engine that lets scientists and engineers describe data‑driven pipelines using a concise DSL built on Groovy. The dataflow model abstracts parallelism, so you focus on how data moves between processes rather than low‑level threading or scheduling.
A single pipeline can run unchanged on a local workstation, on traditional HPC schedulers (SLURM, SGE, etc.), on cloud batch services (AWS, Azure, Google) or on a Kubernetes cluster. Dependency management is handled through Docker, Singularity, Conda, Spack, Podman and other container or package systems, guaranteeing reproducible environments. The community‑driven nf‑core collection provides ready‑made, high‑quality pipelines for bioinformatics and beyond, while the active forum and Slack channel offer rapid support.
Researchers needing reproducible analyses, data scientists scaling workloads, and teams operating across heterogeneous compute resources all gain from Nextflow’s portability, robust execution engine, and strong ecosystem.
When teams consider Nextflow, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Genome variant calling at scale
Run a reproducible variant‑calling pipeline on local, SLURM, or AWS Batch without rewriting code.
RNA‑seq analysis across cloud and HPC
Process thousands of samples using nf‑core RNA‑seq workflow, leveraging Docker containers for consistent environments.
Metagenomics assembly on Kubernetes
Deploy a metagenomic assembly pipeline on a Kubernetes cluster, automatically handling resource allocation.
Machine‑learning model training with dataflow
Orchestrate preprocessing, training, and evaluation steps across distributed nodes, ensuring reproducibility via Conda environments.
Pipelines are defined using Nextflow’s DSL, which extends Groovy; you can embed any command‑line tool or script language.
No. Nextflow runs locally, on HPC schedulers, or on any supported cloud batch service; you choose the executor that fits your environment.
It captures the exact versions of containers, Conda environments, or software modules used for each process, and tracks pipeline code via version control.
Yes. You can reference any public or private Docker/Singularity image directly in the process definition.
Nextflow is primarily CLI‑driven; visualisation tools exist (e.g., Tower) but are separate from the core engine.
Project at a glance
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