Flowfile

A visual ETL tool that combines drag-and-drop workflow building with the speed of Polars dataframes. Build data pipelines visually, transform data using powerful nodes, and analyze results - all without writing code.

Flowfile Interface

Why Flowfile?

Build powerful data pipelines without writing code, powered by the speed of Polars

🎨

Visual Pipeline Design

Drag and drop nodes to create complex data transformations. See your data flow in real-time with instant previews at each step.

Blazing Fast Performance

Built on Polars for lightning-fast data processing. Handle millions of rows with ease using optimized columnar operations.

🔄

Flow to Code

Export your visual flows as Python/Polars code. Deploy workflows anywhere without Flowfile dependencies.

🔌

Database Integration

Connect to PostgreSQL, MySQL, and more. Read, transform, and write data seamlessly between databases and files.

🐍

Code to Flow

Use the FlowFrame API to build pipelines programmatically. Visualize your code as a flow graph instantly.

👩‍💻

Python API

Full Python API with Polars compatibility. Build pipelines programmatically and seamlessly switch between code and visual editing.

Build Pipelines Your Way

Use the visual designer for exploration or write code for automation - seamlessly switch between both

📊 Visual Approach

  • Drag and drop nodes to build workflows
  • Configure transformations with intuitive forms
  • Preview data at each step instantly
  • Export your pipeline as Python code
  • Perfect for exploration and prototyping

🐍 Code Approach

import flowfile as ff

df = ff.read_csv("data.csv")
result = df.filter(
    ff.col("amount") > 1000
).group_by("region").agg(
    ff.col("amount").sum()
)

# Visualize your pipeline
ff.open_graph_in_editor(result.flow_graph)

See It For Yourself

Start rediscovering how we bridge the gap between business users and technical users.

5 min
to first pipeline
100%
Familiar API
0
vendor lock-in
Try Interactive Tutorial Browse Examples

Free, open-source and customizable