Flywheel vs DIY Scripts
Should you build data pipelines yourself or use automation? An honest comparison for growing companies.
TL;DR
DIY works when you have a single simple integration and available engineering bandwidth. Most companies outgrow this quickly - managing 5-10 integrations requires significant ongoing maintenance.
Flywheel makes sense when you'd rather focus on product than maintain data infrastructure. Free for 10K rows/month, set up in under an hour, zero maintenance required.
Real Cost Comparison
Scenario: Syncing 3 data sources (Postgres, Stripe, Google Analytics) to BigQuery
DIY Python Scripts:
• Initial build: 2-3 days per integration = 6-9 days
• At $150/hr contractor rate: $7,200 - $10,800
• Monthly maintenance: 4-8 hours = $600 - $1,200/mo
• API changes/debugging: 2-4 hours/mo = $300 - $600/mo
First year cost: $18,000 - $33,000
Flywheel:
• Initial setup: 1-2 hours = Free tier
• Monthly cost: $0 (Free tier: 10K rows)
• or Pro tier: $99/mo for 1M rows
• Maintenance: $0 (handled by Flywheel)
• API changes: $0 (handled by Flywheel)
First year cost: $0 - $1,188
Key insight: DIY appears low-cost but typically costs 15-30x more in engineering time
Feature Comparison
| Feature | Flywheel | DIY Scripts |
|---|---|---|
| Setup time | 1-2 hours | 2-3 days per integration |
| Code to maintain | 0 lines | 500-2000 lines per integration |
| Error handling | You build it | |
| API changes | Handled automatically | You fix it |
| Schema detection | You build it | |
| Retry logic | You build it | |
| Monitoring | You build it | |
| Deduplication | You build it | |
| Scheduling | Cron built-in | You build it (cron/Airflow) |
| Field transformations | JSONata + visual | Custom Python code |
| OAuth handling | You implement OAuth flow | |
| Uptime SLA | 99.9% | Depends on your infra |
Honest Pros & Cons
DIY Python Scripts
Pros
- • Complete control and customization
- • No recurring costs (just your time)
- • Learn valuable engineering skills
- • No vendor dependency
- • Can optimize for specific edge cases
Cons
- • Significant initial development time
- • Ongoing maintenance burden
- • Requires handling all API changes
- • Unpredictable debugging needs
- • Difficult to scale to many integrations
- • Each new source requires similar effort
Flywheel
Pros
- • Fast setup (typically under an hour)
- • Zero maintenance required
- • Free tier for getting started
- • Built-in error handling and retries
- • Frees engineering time for product work
- • Scales easily to 10+ integrations
Cons
- • Less control than custom code
- • Monthly cost once you exceed free tier
- • Learning curve for platform specifics
- • Vendor dependency
Which Should You Choose?
Build it yourself if you:
- ✓ Have a single simple integration
- ✓ Have available engineering bandwidth
- ✓ Need highly custom logic
- ✓ Want to build data engineering expertise
- ✓ Are pre-revenue with minimal budget
- ✓ Have time for ongoing maintenance
Note: Most companies find DIY doesn't scale beyond 2-3 integrations.
Use Flywheel if you:
- ✓ Have 2+ data sources to sync
- ✓ Value engineering time
- ✓ Want to focus on product development
- ✓ Need a solution running within days
- ✓ Prefer not to maintain pipeline code
- ✓ Plan to scale integrations over time
Start free (10K rows/month) - validate value before upgrading.
Hidden Costs of DIY
1. Opportunity Cost
Time spent building data pipelines is time not spent on product features, customer acquisition, or business growth. Engineering hours are your most valuable resource.
2. Technical Debt
Initial “quick scripts” become critical dependencies. Over time, these accumulate complexity and become difficult to maintain or modify without risk.
3. Linear Scaling Costs
Each new integration requires similar development time. The first integration takes 3 days, the second takes 3 days, and the third takes 3 days. Costs scale linearly with each data source.
4. Unexpected Maintenance
API rate limits change, schemas drift, authentication tokens expire - custom scripts require ongoing maintenance at unpredictable times, often outside business hours.
Common Questions
Can I start with DIY and switch to Flywheel later?
Yes. Many teams start with a custom script for their first integration, then migrate to Flywheel when managing 2-3 sources. Migration typically takes a few hours.
What if I need custom logic Flywheel doesn't support?
Flywheel supports JSONata expressions for complex transformations. For highly specific requirements, you can use our API to execute custom logic. Most teams find the built-in transformation capabilities sufficient.
Is DIY better for building technical expertise?
If learning data engineering is a priority, DIY provides valuable experience. However, if your primary goal is business growth, focusing engineering time on product development typically provides better returns. Custom pipeline development can be revisited later with dedicated data engineering resources.
How do I justify Flywheel's cost?
Start with the free tier (10K rows/month) to validate value. When upgrading to Pro ($99/month), compare against engineering time: 8-16 hours monthly at $150/hour equals $1,200-$2,400 in time costs avoided.
Try Flywheel Risk-Free
Free tier: 10,000 rows/month with all features. No credit card required. Set up in under an hour.