Hamilton vs Singer: Pricing and Ratings Compared (2026)
Entry prices and free plans as read on each vendor's pricing page, and user ratings as published on review sites, for Hamilton and Singer side by side. This page compares data; it is not a hands-on review.
On the data: On the data below the two are close or not directly comparable, so we do not name a winner for this pair.
Short on time? Here's the quick answer
Based on published vendor pricing and features and on public review data, here's who should pick what:
Hamilton
A general-purpose framework to write dataflows using regular Python functions.
Best for you if:
- • You want facilitates collaboration with flat dataflows and clear dependencies
Singer
Open-source data integration framework
Best for you if:
- • You want open source ETL spec
| At a Glance | Hamilton | Singer |
|---|---|---|
Starts at | Free 100% free | Free 100% free |
Category | ETL & Data Pipelines Workflow Automation | ETL & Data Pipelines Data & Databases |
Rating | n/a | n/a |
Free plan | Yes | Yes |
Choose Hamilton or Singer?
Choose Hamilton if
- You want facilitates collaboration with flat dataflows and clear dependencies
- You want reduces development time through reusability of dataflows
Choose Singer if
- You want open source ETL spec
- You want many taps/targets
In-Depth Analysis
Hamilton
A general-purpose framework to write dataflows using regular Python functions.
Strengths
- Pro: Facilitates collaboration with flat dataflows and clear dependencies
- Pro: Reduces development time through reusability of dataflows
- Pro: Prevents vendor lock-in with flexible integration options
- Pro: Scales dataflows seamlessly via remote execution and specialized engines
- Pro: Provides clear visualization and documentation directly from code
Weaknesses
- Con: Requires type-annotated Python functions
- Con: Currently in incubation phase (Apache Incubating)
Key features
Singer
Open-source data integration framework
Singer's pricing is exceptionally generous, as it is entirely free and open-source.
Strengths
- Pro: Open source ETL spec
- Pro: Many taps/targets
- Pro: Community driven
- Pro: Good flexibility
- Pro: Meltano integration
Weaknesses
- Con: Setup complexity
- Con: Tap quality varies
- Con: Documentation gaps
- Con: Maintenance needed
- Con: Learning curve
Key features
Plans and prices: Hamilton vs Singer
| Tool | Plans and prices | Source |
|---|---|---|
| Hamilton | No plan prices on file | hamilton.dagworks.io |
| Singer |
| singer.io read Oct 6, 2026 |
Prices as read on each vendor's own pricing page on the date shown. Plans are listed per tool and are not matched against the other tool's plans: a plan name or price in one column says nothing about the same row in the other. Details on Hamilton pricing and Singer pricing.
Key Takeaways
Hamilton
- Choose if you want a general-purpose framework to write dataflows using regular Python functions
Singer
- Choose if you want open-source data integration framework
What the data shows
On the data below the two are close or not directly comparable, so we do not name a winner for this pair.
- Both have a free plan.
Criteria: user rating (only above 20 reviews on both sides, gap of 0.2 or more), entry price (only on the same billing basis), free plan. How we rate
Frequently Asked Questions
How do Hamilton and Singer compare in 2026?
On the data below the two are close or not directly comparable, so we do not name a winner for this pair. Both have a free plan.
What are Hamilton and Singer used for?
Hamilton: A general-purpose framework to write dataflows using regular Python functions. Singer: Open-source data integration framework.
What does Hamilton cost vs Singer?
Hamilton is free. Singer is free. Prices read on the vendors' pricing pages, latest check Oct 6, 2026.
What's the main difference between Hamilton and Singer?
Hamilton's main strength: facilitates collaboration with flat dataflows and clear dependencies. Singer's main strength: open source ETL spec.