ETL Pipelines, Made Simple β scale as you need, without the hassle.

Airtruct is a modern, open-source data pipeline tool designed to be a powerful and efficient alternative to tools like Airbyte and Fivetran. It empowers data analysts and scientists to easily build and manage data streams with a user-friendly, DAG-style UI.
Key Features
- Visual DAG-style Stream Builder: Intuitive UI to visually create and manage data pipelines using a Directed Acyclic Graph (DAG) interface.
- Powerful In-Pipeline Transformations: Utilize Bloblang, a lightweight, JSON-like DSL, for efficient data transformation and enrichment within the pipeline. Bloblang offers built-in mapping, filtering, and conditional logic, often replacing the need for separate transformation tools like dbt.
- Flexible Subprocess Processor: Integrate processors or enrichers developed in any programming language. Communication occurs via stdin/stdout, ensuring language-agnostic compatibility.
- Native HTTP Input: Accept data over HTTP, making it ideal for handling webhooks and streaming data sources.
- Horizontally Scalable Worker Pool Architecture: Scale your data processing capabilities with a horizontally scalable worker pool.
- Delivery Guarantee: Ensures reliable data delivery.
- Buffering and Caching: Optimizes performance through buffering and caching mechanisms.
- Robust Error Handling: Provides comprehensive error handling capabilities.
Why Airtruct?
Airtruct stands out from traditional ETL tools through its completely free Apache 2.0 license and zero operational overhead. Unlike Docker-heavy alternatives that require complex setups, Airtruct runs as a single lightweight binary with no dependencies. It features native transformation capabilities using the powerful Bloblang DSL, eliminating the need for separate tools like dbt, while supporting custom processors in any programming language through simple stdin/stdout communication. With built-in HTTP input support for webhooks, a full DAG-style visual interface, and comprehensive observability (metrics, tracing, and logs), Airtruct delivers enterprise-grade functionality without the enterprise complexity. Its horizontally scalable worker pool architecture ensures you can handle massive workloads while maintaining the simplicity that makes data engineering enjoyable again.
Architecture
Airtruct employs a Coordinator & Worker model:
- Coordinator: Handles pipeline orchestration and workload balancing across workers.
- Workers: Stateless processing units that auto-scale to meet processing demands.
This architecture is lightweight and modular, with no Docker dependency, enabling easy deployment on various platforms, including Kubernetes, bare-metal servers, and virtual machines.
graph TD;
A[Coordinator] <--> B[Worker 1];
A[Coordinator] <--> C[Worker 2];
A[Coordinator] <--> D[Worker 3];
A[Coordinator] <--> E[Worker ...];
%% Styling for clarity
class A rectangle;
class B,C,D,E rectangle;
Airtruct is designed for high performance and scalability:
- Go-native: Built as a single binary with no VM or container overhead, keeping things light and fast.
- Memory-safe and Low CPU Usage: Engineered for efficient resource utilization.
- Smart Load Balancing: Worker pool model with intelligent load balancing.
- Parallel Execution Control: Fine-grained control over parallel processing threads.
- Real-time & Batch Friendly: Supports both real-time and batch data processing.
Quick Start
π¦ 1. Download the Latest Binary
You can get started with AirTruct quickly by downloading the precompiled binary:
- Go to the Releases page.
- Find the latest release.
- Download the appropriate binary for your operating system (Windows, macOS, or Linux).
After downloading and extractict binary:
- On Linux/macOS: make the binary executable:
chmod +x [airtruct-binary-path]
- On Windows: just run the .exe file directly.
βοΈ 2. Set up SQLite or other full database URI
If you want to quickly start with SQLite as your database, set the DATABASE_URI environment variable before running the coordinator otherwise Airtruct will store data in memory and you will lose the data after process stopped:
export DATABASE_URI="file:./airtruct.sqlite?_foreign_keys=1&mode=rwc"
π 3. Run coordinator & worker
Start the AirTruct coordinator by specifying the role and gRPC port:
- optionatlly you can specify
-http-port if you want to run console different port that 8080
[airtruct-binary-path] -role coordinator -grpc-port 50000
Now run the worker with same command but role worker (if you are running both on the same host consider using different GRPC port).
[airtruct-binary-path] -role worker -grpc-port 50001
You're all set, just open the console http://localhost:8080 β happy building with AirTruct! π
Example: Kafka to PostgreSQL Pipeline
Want to see Airtruct in action? Check out our comprehensive Kafka to PostgreSQL streaming example that demonstrates a complete end-to-end pipeline. This tutorial shows you how to stream events from Kafka through Avro schema registry processing directly into PostgreSQL, showcasing Airtruct's real-time processing capabilities and easy configuration.
Documentation
Documentation is currently in progress.
Feel free to open issues if you have specific questions!
Contributing
We welcome contributions! Please check out CONTRIBUTING (coming soon) for guidelines.
License
This project is licensed under the Apache 2.0 License. See the LICENSE file for details.