Why DLT Beats Fivetran: Save €18,000 Per Year on Data Pipelines
The hidden cost of data movement
Here's an uncomfortable truth: Getting data from point A to point B doesn't create business value. The insights you extract from that data do.
Yet many companies spend €1,500+ per month on tools like Fivetran just to move data around. That's €18,000 per year on the non-value-adding part of your data stack.
Why traditional tools are expensive
Tools like Fivetran charge based on:
- Number of connectors - Each data source adds cost
- Rows processed - Your data growth = higher bills
- Premium features - Advanced transformations cost extra
A typical mid-sized company with 10-15 data sources easily reaches €1,500/month. Scale up, and costs balloon to €3,000-5,000/month.
Enter dlt: the open-source alternative
DLT (Data Load Tool) is a Python library for building data pipelines. It's free, open-source, and backed by a thriving community (~5,000 GitHub stars).
What dlt offers
- Free forever - No per-connector or per-row fees
- 100+ verified sources - APIs, databases, files, cloud services
- Automatic schema evolution - Adapts to source changes
- Built-in data quality - Validation and monitoring included
- Python-native - Customize anything, integrate with your code
- Version controlled - All pipelines are code in Git
The real cost comparison
Fivetran
€1,500/month
€18,000 per year
- Limited to pre-built connectors
- Customization requires paid support
- Vendor lock-in
- Costs scale with data volume
Dlt + our platform
~€100/month
€1,200 per year
- 100+ connectors + custom sources
- Fully customizable (it's Python)
- No vendor lock-in
- Fixed compute costs
Save €16,800/year
But is it production-ready?
Yes. DLT is used by companies running billions of rows daily. It's built by data engineers who understand production requirements:
- Incremental loading for efficiency
- Automatic retries and error handling
- Schema evolution without breaking pipelines
- Built-in observability and logging
- Active community support
Our approach: dlt + modern infrastructure
We run DLT pipelines in Docker containers on Google Cloud Run:
- Cloud Run Jobs - Serverless compute, pay only when running
- Cloud Scheduler - Trigger workflows on your schedule
- Cloud Workflows - Trigger DBT once DLT is done
- Git version control - Track every change
This architecture is lightweight, scalable, and costs a fraction of traditional platforms.
What about dbt?
DLT gets data into your warehouse. DBT transforms that raw data into insights. Together, they form a complete, cost-efficient stack.
Learn more about how DBT turns data into business value.
The bottom line
Data ingestion is a commodity. Don't overpay for it.
With DLT and modern cloud infrastructure, you get enterprise-grade capabilities at a fraction of the cost. Save €16,800+ per year and invest that budget where it creates real value: in analytics, ML models, and insights.