Dingo
A Comprehensive Data Quality Evaluation Tool
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
Verified · Jun 21, 2026Overview
What is Dingo?
Dingo is an open-source tool designed to evaluate the quality of data in various datasets. It helps developers and data scientists ensure that their data meets high standards for accuracy, completeness, and consistency.
Key differentiator
“Dingo stands out as a comprehensive, open-source solution for evaluating the quality of datasets, offering customizable checks and detailed reporting.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Primary development and maintenance focus is on Python, with other languages having minimal or no official support
GitHub repository has few contributors and open issues remain unresolved for extended periods
Fit analysis
Who is it for?
✓ Best for
Developers working on projects that require high-quality, consistent data inputs
Data scientists who need to validate the integrity of their datasets before analysis
✕ Not a fit for
Projects requiring real-time data quality monitoring and correction
Teams with limited technical expertise in setting up and configuring self-hosted tools
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Works well with
Next step
Get Started with Dingo
Step-by-step setup guide with code examples and common gotchas.