Dev tools · alternatives · 2026
24 alternatives to Apache Airflow on Astronomer
Write and deploy custom ETL pipelines in Python
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Apache Airflow on Astronomer launched in 2018; newer entries below may have overtaken it.
- 1
The easiest way to run Apache Airflow on your infrastructure
2018 · astronomer.io · its alternatives →
- 2
afctl helps to manage and deploy Apache Airflow projects faster and smoother. - qubole/afctl
2020 · github.com · its alternatives →
- 3
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Visualize Airflow's schedule by exporting future DAG runs as events to Google Calendar. - domenp/aircal
2020 · github.com · its alternatives →
- 5
DAGForge▲8Built DAGForge to make generating and validating Airflow DAGs much faster. Most AI tools produce broken or incomplete DAGs, so I added: Airflow-aware validation (operators, imports, params) Syntax + security checks Deterministic JSON parsing to avoid hallucinations Support for local or cloud LLMs Would love feedback from data engineers and Airflow users. Demo: https://dagforge.com
Nov 2025 · dagforge.com · its alternatives →
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Hey HN, I'm really proud to share with you my new open source project: Kestra https://github.com/kestra-io/kestra I created a few years ago a successful open source AKHQ project: https://github.com/tchiotludo/akhq (renamed from KafkaHQ) which has been adopted by big companies like Best Buy, Pipedrive, BMW, Decathlon and many more. 2300 stars, 120 contributors, 10M docker downloads, much more than I expected. Now let's talk about Kestra, an infinitely scalable orchestration and scheduling platform for creating, running, scheduling and monitoring…
2022 · github.com · its alternatives →
- 8
I have created a Cron alternative that runs DAGs (Directed acyclic graph) defined in a simple YAML format. Why not Airflow? Airflow and other similar tools are powerful and valuable, but in most cases, they require writing code to manage workflows. Our ETL pipeline is already hundreds of thousands of lines of complex code in Perl and shell scripts. Adding another layer of Python on top of this would make it difficult to maintain. Instead, we needed a more lightweight solution. So we developed Dagu, which requires no coding, and is easy-to-use and self-contained, making it ideal for smaller…
2022 · github.com · its alternatives →
- 9FO
2022 · medium.com · its alternatives →
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- 11
2022 · typhoon-data-org.github.io · its alternatives →
- 12
Minimal distributed configuration management in bash - frameable/aviary.sh
2020 · github.com · its alternatives →
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🧙 Build, run, and manage data pipelines for integrating and transforming data. - mage-ai/mage-ai
2022 · github.com · its alternatives →
- 14
Managed RAG pipelines, made easy
2025 · blog.cloudflare.com · its alternatives →
- 15
buildpipe▲116Compose, run and automate multi step AI developer workflows
May 2026 · buildpipe.com · its alternatives →
- 16
PipeOps▲102No code tool for cloud deployment & infrastructure mgmt
2023 · pipeops.io · its alternatives →
- 17
Hi HN. Today we released Dagster Cloud to general availability [1], which includes a new feature you can try that we're calling Branch Deployments. Branch Deployments were inspired by Vercel's Preview Deployments feature and deep GitHub integration. We're hoping we can bring a similar developer experience improvement to the data domain. Let us know your feedback! [1] https://dagster.io/blog/dagster-cloud-ga-launch
2022 · twitter.com · its alternatives →
- 18
Nitric Deploy▲197The right infrastructure, auto-provisioned in your cloud
2022 · nitric.io · its alternatives →
- 19
We’re Robin, Louis, and Thomas. Pipelex is a DSL and a Python runtime for repeatable AI workflows. Think Dockerfile/SQL for multi-step LLM pipelines: you declare steps and interfaces; any model/provider can fill them. Why this instead of yet another workflow builder? - Declarative, not glue code: you state what to do; the runtime figures out how. - Agent-first: each step carries natural-language context (purpose, inputs/outputs with meaning) so LLMs can follow, audit, and optimize. Our MCP server enables agents to run pipelines but also to build new pipelines on demand. - Open…
Oct 2025 · github.com · its alternatives →
- 20PP
I’ve found that I don’t have any context about the data in my pipelines only know if the pipeline is successful or not. So I built panda-patrol which allows you to monitor each node in your DAG, use AI to generate data tests for your data, store data profiles, and more. All with this comes with dashboards and alerts. You can easily drop it into your Python-based data pipeline (i.e. Airflow, Dagster, Prefect, etc.) and just run your pipelines are you normally would — but with monitoring and more context. Hope its valuable to some people
2023 · panda-patrol.vercel.app · its alternatives →
- 21
Dagster Cloud▲112The data orchestrator that puts developer experience first
2022 · dagster.io · its alternatives →
- 22
Amazon AppFlow▲110Securely integrate apps and automate data flows without code
2020 · aws.amazon.com · its alternatives →
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Flowpipe [1] is a new open source [2] cloud scripting engine from Turbot [3]. Some of you may already use Steampipe [4], our open-source [5] tool to live query cloud APIs. We believe DevOps teams need an easier way to orchestrate their cloud, build workflows and respond to events. But - because it's DevOps - that must be in code. In Flowpipe, pipelines are written in HCL and use simple primitives for HTTP requests, executing containers, running Lambda-compatible functions, querying databases like Steampipe and more. We have also published a large ecosystem of open source Flowpipe Mods [6].…
2023 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →