Windmill is a developer platform for writing scripts, building flows, and creating internal apps, all in code. Kestra is a workflow orchestration platform built around declarative YAML, 1200+ pre-built plugins, and first-class event-driven triggers. Both run workflows; they're built for different teams with different scope requirements.
YAML describes what should run, when, and in what order. Business logic lives in your existing Python, SQL, Bash, or dbt scripts. No framework wrappers, no code refactoring required. Kestra handles scheduling, retries, dependencies, and observability as first-class YAML primitives, and scales from a single pipeline to 100,000 concurrent tasks.
Windmill is an all-in-one platform for scripts, flows, and internal apps. Write steps in Python, TypeScript, Go, or Bash; connect them in a visual DAG editor; optionally build a low-code UI on top. Windmill is built for developer productivity and internal tooling as much as for workflow automation. The authoring model is code throughout.
Windmill offers both a cloud service (windmill.dev) and a self-hosted Docker deployment. This comparison uses their cloud path—sign up via SSO, write step code in the web IDE, and wire steps into a flow.
curl -o docker-compose.yml \https://raw.githubusercontent.com/kestra-io/kestra/develop/docker-compose.ymldocker compose up
# Open localhost:8080# Pick a Blueprint, run it. Done.Download the Docker Compose file, spin it up, and you're ready (database and config included). Open the UI, pick a Blueprint, run it. No code to write before your first workflow executes.
# Cloud: sign up at windmill.dev (free tier available)# Then in the web IDE:
# Step 1: Write a script step (Python or TypeScript)# Step 2: Create a flow, add the step# Step 3: Wire step inputs/outputs# Step 4: Add a schedule trigger# Step 5: Run and monitor
# Self-hosted option:docker compose up -d# Then go through the same authoring steps...Sign up via GitHub SSO, enter the web IDE, write your first script step, connect it into a flow, wire inputs and outputs between steps, and run. Each step is code you write; there are no pre-built plugin tasks to drop in for dbt, Airbyte, or Snowflake.
YAML is readable on day 1. Our docs are embedded in the UI for easy reference, the AI Copilot writes workflows for you, or start with our library of Blueprints. No code required to run a dbt model, trigger an Airbyte sync, or load data to Snowflake.
Windmill flows are built by writing individual script steps and wiring their inputs and outputs in the visual flow editor. Each integration with dbt, Slack, or an external system requires writing and maintaining the connection code yourself. The steps are readable to developers; the flow topology lives in the visual editor or the underlying OpenFlow JSON.
Orchestrate data pipelines, infrastructure operations, business processes, and AI workflows in one unified platform. Event-driven at its core, with native triggers for S3, Kafka, webhooks, and database changes. 1200+ plugins cover the full data and infrastructure stack, all defined in YAML.
A developer platform that combines script execution, flow orchestration, and internal app building in one workspace. Teams get scripts and lightweight automations alongside a drag-and-drop UI builder. Native data pipeline integrations (dbt, Airbyte, Snowflake) require writing and maintaining connection code rather than dropping in a plugin task.
| | | |
|---|---|---|
| Workflow definition | Declarative YAML | Code (Python, TypeScript, Go, Bash) + visual editor |
| Native data pipeline plugins | 1200+ plugins (dbt, Airbyte, Spark, Snowflake, Kafka) | No pre-built plugin library; integrations require custom code |
| Event-driven triggers | Native (S3, Kafka, webhooks, database changes, schedules) | Webhooks, schedules, and HTTP routes |
| Internal app builder | Kestra Apps (workflow trigger forms) | ✓ Low-code drag-and-drop app builder |
| Languages supported | Any (scripts run in isolated containers, no SDK required) | Python, TypeScript, Go, PHP, Bash, SQL, Rust, C# |
| Multi-tenancy | Namespace isolation + RBAC out-of-box | Workspaces with role-based access |
| Deployment complexity | Docker Compose (two commands) | Docker Compose or Kubernetes |
| Infrastructure automation | Native support | Possible via script steps, not a primary use case |
| Self-service for non-engineers | Kestra Apps with parameter forms | Auto-generated UIs from script signatures |
Kestra delivers end-to-end automation with the robustness we need at our scale. Few companies operate at this level, especially in AI/ML.
Kestra ships native plugin tasks for dbt, Airbyte, Spark, Snowflake, BigQuery, Kafka, Databricks, and 1200+ more. Drop one into a YAML workflow and it runs with no connection code to write or API docs to parse. Every integration is a pre-built task type, not custom code your team writes and maintains.
A Kestra workflow is a YAML file that any team member can read and modify; ops teams can trigger runs from the UI without touching the implementation. Business users interact with workflows through Kestra Apps — no-code forms that trigger, monitor, and collect input without exposing the underlying YAML.
S3 file arrivals, Kafka message consumption, database row changes, and webhook callbacks are YAML trigger blocks sitting alongside the task list in the same file. Kestra's trigger system covers the reactive patterns data teams actually need without writing any polling code or managing external event listeners.
Find answers to your questions right here, and don't hesitate to Contact Us if you couldn't find what you're looking for.
See how Kestra can simplify your workflows—and scale beyond developer scripts.