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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A language and runtime for distributed, incremental data processing in the cloud
| Date | Stars |
|---|---|
| 2026-07-24 | 975 |
| 2026-07-25 | 975 |
| 2026-07-28 | 975 |
| 2026-07-30 | 975 |
| 2026-08-06 | 975 |
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 [](https://gitter.im/grailbio/reflow?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [](https://travis-ci.org/grailbio/reflow) Reflow is a system for incremental data processing in the cloud. Reflow enables scientists and engineers to compose existing tools (packaged in Docker images) using ordinary programming constructs. Reflow then evaluates these programs in a cloud environment, transparently parallelizing work and memoizing results. Reflow was created at [GRAIL](http://grail.com/) to manage our NGS (next generation sequencing) bioinformatics workloads on [AWS](https://aws.amazon.com), but has also been used for many other applications, including model training and ad-hoc data analyses. Reflow comprises: - a functional, lazy, type-safe domain specific language for writing workflow programs; - a runtime for evaluating Reflow programs [incrementally](https://en.wikipedia.org/wiki/Incremental_computing), coordinating cluster execution, and transparent memoization; - a cluster scheduler to dynamically provision and tear down resources from a cloud provider (AWS currently supported). Reflow thus allows scientists and engineers to write straightforward programs and then have them transparently executed in a cloud environment. Programs are automatically parallelized and distributed across multiple machines, and redundant computations (even across runs and users) are eliminated by its memoization cache. Reflow evaluates its programs [incrementally](https://en.wikipedia.org/wiki/Incremental_computing): whenever the input data or program changes, only those outputs that depend on the changed data or code are recomputed. In addition to the default cluster computing mode, Reflow programs can also be run locally, making use of the local machine's Docker daemon (including Docker for Mac). Reflow was designed to support sophisticated, large-scale bioinformatics workflows, but should be widely applicable to scientific and engineering computing workloads. It was built using [Go](https://golang.org). Reflow joins a [long list](https://github.com/pditommaso/awesome-pipeline) of systems designed to tackle bioinformatics workloads, but differ from these in important ways: - it is a vertically integrated system with a minimal set of external dependencies; this allows Reflow to be "plug-and-play": bring your cloud credentials, and you're off to the races; - it defines a strict data model which is used for transparent memoization and other optimizations; - it takes workflow software seriously: the Reflow DSL provides type checking, modularity, and other constructors that are commonplace in general purpose programming languages; - because of its high level data model and use of caching, Reflow computes [incrementally](https://en.wikipedia.org/wiki/Incremental_computing): it is always able to compute the smallest set of operations given what has been computed previously. ## Table of Contents - [Quickstart - AWS](#quickstart---aws) - [Simple bioinformatics workflow](#simple-bioinformatics-workflow) - [1000align](#1000align) - [Documentation](#documentation) - [Developing and building Reflow](#developing-and-building-reflow) - [Debugging Reflow runs](#debugging-reflow-runs) - [A note on Reflow's EC2 cluster manager](#a-note-on-reflows-ec2-cluster-manager) - [Setting up a TaskDB](#setting-up-a-taskdb) - [Support and community](#support-and-community) ## Getting Reflow You can get binaries (macOS/amd64, Linux/amd64) for the latest release at the [GitHub release page](https://github.com/grailbio/reflow/releases). If you are developing Reflow, or would like to build it yourself, please follow the instructions in the section "[Developing and building Reflow](#developing-and-building-reflow)." ## Quickstart - AWS Reflow is distributed with an EC2 cluster manager, and a
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matched fp:6c5ab091e7be20c1, topic:scientific-computing, readme:bioinformatics
