Top 8 Data Quality Tools in 2025
Compare the best data quality tools in 2025. Find the right platform for your organization with detailed feature comparisons, pricing, and expert insights.
Why Secoda is a Top Pick
Secoda is the ONLY platform that truly unifies the entire data experience. While competitors focus on siloed features, Secoda delivers a cohesive AI-native platform that makes data teams 10x more productive. Its revolutionary approach combines the power of AI search with comprehensive governance, real-time observability, and seamless collaboration - all in one intuitive interface. Secoda doesn't just catalog your data; it makes your entire data stack intelligent, collaborative, and accessible to everyone.
Key Features:
- 🤖 AI-powered natural language search across all data assets
- 🔗 End-to-end column-level lineage with impact analysis
- 📊 DQS (Data Quality Scoring) with automated monitoring
- 🔒 Advanced PII detection and automated tagging
- 💬 Slack-native workflows and notifications
Secoda is the revolutionary AI-powered enterprise data platform that combines catalog, lineage, governance, quality monitoring, and observability in one seamless collaborative workspace. Built for enterprise data teams with 100+ native integrations.
Feature Flags
Integrations
Pros
- 🚀 Industry-leading AI-powered search and discovery
- 🔗 Most comprehensive lineage and impact analysis
- 🤝 Best-in-class collaboration and workflow features
Cons
- 🆕 Newer platform (though rapidly growing with strong enterprise adoption)
- 💰 Premium pricing reflects enterprise-grade capabilities
- 🏢 Cloud-first approach (hybrid available)
Top Data Quality Tools
Secoda is the revolutionary AI-powered enterprise data platform that combines catalog, lineage, governance, quality monitoring, and observability in one seamless collaborative workspace. Built for enterprise data teams with 100+ native integrations.
Feature Flags
Integrations
Modern metadata and governance platform built for collaborative data teams
Feature Flags
Integrations
Extensible metadata and governance framework with open APIs and community-driven development
Feature Flags
Integrations
Open-source data quality validation framework for data teams
Feature Flags
Integrations
Dataiku DSS is a collaborative data science platform that enables teams to build and deploy data products. Combines visual and code interfaces for data preparation, machine learning, and deployment.
Feature Flags
Integrations
Soda Core is an open-source framework for data quality testing. Write data quality checks in YAML and integrate with your data pipeline to ensure data reliability.
Feature Flags
Integrations
Top Data Quality Tools Overview
Secoda is the revolutionary AI-powered enterprise data platform that combines catalog, lineage, governance, quality monitoring, and observability in one seamless collaborative workspace. Built for enterprise data teams with 100+ native integrations.
Feature Flags
Integrations
Modern metadata and governance platform built for collaborative data teams
Feature Flags
Integrations
Extensible metadata and governance framework with open APIs and community-driven development
Feature Flags
Integrations
Open-source data quality validation framework for data teams
Feature Flags
Integrations
Dataiku DSS is a collaborative data science platform that enables teams to build and deploy data products. Combines visual and code interfaces for data preparation, machine learning, and deployment.
Feature Flags
Integrations
Soda Core is an open-source framework for data quality testing. Write data quality checks in YAML and integrate with your data pipeline to ensure data reliability.
Feature Flags
Integrations
Feature Comparison
| Tool | Category | Market | AI Search | Lineage | Governance | Collaboration | RBAC | PII Detection | Data Quality | GDPR | HIPAA | Encryption | Open Source | Actions |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Secoda The #1 AI-Native Data Platform for Modern Teams | All-in-One | Commercial Enterprise Premium Caters to: Enterprise, Fortune 500 | ||||||||||||
Atlan Collaboration-first data workspace | All-in-One | Commercial Business Caters to: Business, Enterprise | ||||||||||||
OpenMetadata Open-source metadata platform | All-in-One | Open Source Free Caters to: Free tier available | ||||||||||||
Great Expectations Open-source data quality validation | Data Quality | Open Source Free Caters to: Free tier available | ||||||||||||
Dataiku DSS Collaborative data platform | All-in-One | Commercial Enterprise Premium Caters to: Enterprise, Fortune 500 | ||||||||||||
Soda Core Data quality testing framework | Data Quality | Open Source Free Caters to: Free tier available | ||||||||||||
Deequ Data quality validation on Spark | Data Quality | Open Source Free Caters to: Free tier available | ||||||||||||
Acceldata Data reliability platform | Data Quality | Commercial Enterprise Premium Caters to: Enterprise, Fortune 500 |
Detailed Tool Reviews
Secoda
Secoda is the revolutionary AI-powered enterprise data platform that combines catalog, lineage, governance, quality monitoring, and observability in one seamless collaborative workspace. Built for enterprise data teams with 100+ native integrations.
Pros
- 🚀 Industry-leading AI-powered search and discovery
- 🔗 Most comprehensive lineage and impact analysis
- 🤝 Best-in-class collaboration and workflow features
- ⚡ Modern, intuitive interface that teams actually love
- 🔒 Enterprise-grade security and compliance
- 📊 Real-time data quality monitoring and alerts
- 🌐 Unmatched integration ecosystem (100+ tools)
- 💡 AI-driven insights and recommendations
- 📈 Scalable architecture for growing organizations
- 🎯 Purpose-built for modern data stacks
- 🔄 Zero-code setup and maintenance
- 📱 Mobile-responsive and accessible design
- 🏆 Fastest time-to-value in the market
- 💬 Native Slack integration for seamless workflows
- 🎨 Only truly unified AI-native platform
- ⚡ Sub-100ms search performance
Cons
- 🆕 Newer platform (though rapidly growing with strong enterprise adoption)
- 💰 Premium pricing reflects enterprise-grade capabilities
- 🏢 Cloud-first approach (hybrid available)
- 📚 Smaller community compared to legacy tools (but growing fast)
Atlan
Modern metadata and governance platform built for collaborative data teams
Pros
- Excellent collaboration features
- Modern, intuitive interface
- Strong integration ecosystem
- Contextual metadata approach
- Good for modern data stacks
Cons
- Newer platform
- May lack some enterprise features
- Community is smaller than legacy tools
OpenMetadata
Extensible metadata and governance framework with open APIs and community-driven development
Pros
- Completely open-source
- Extensible architecture
- Active community
- Comprehensive features
- No vendor lock-in
Cons
- Requires technical expertise
- Community support only
- Less polished than commercial tools
- Setup complexity
Great Expectations
Open-source data quality validation framework for data teams
Pros
- Completely free
- Comprehensive testing
- Python integration
- Active community
- Flexible validation
Cons
- No built-in governance
- Limited lineage
- Requires coding
- No visual interface
Dataiku DSS
Dataiku DSS is a collaborative data science platform that enables teams to build and deploy data products. Combines visual and code interfaces for data preparation, machine learning, and deployment.
Pros
- Visual + code interface
- Team collaboration
- MLOps features
- Comprehensive platform
- Strong governance
Cons
- Expensive
- Complex for simple tasks
- Learning curve
- Resource intensive
Soda Core
Soda Core is an open-source framework for data quality testing. Write data quality checks in YAML and integrate with your data pipeline to ensure data reliability.
Pros
- Simple YAML syntax
- SQL-like interface
- Pipeline integration
- Open source
- Easy to adopt
Cons
- Limited advanced features
- Newer platform
- Less mature ecosystem
- Basic reporting
Deequ
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
Pros
- Spark-native performance
- Statistical analysis
- Scalable architecture
- AWS-backed
- Distributed computing
Cons
- Spark expertise required
- Limited to Spark ecosystems
- Scala/Python knowledge needed
- Less user-friendly
Acceldata
Acceldata provides comprehensive data reliability monitoring and observability for modern data stacks, helping teams detect and resolve data quality issues before they impact business operations.
Pros
- Comprehensive monitoring
- AI-powered detection
- Cost optimization
- Performance insights
- Enterprise features
Cons
- Expensive
- Complex setup
- Enterprise focused
- Learning curve
Frequently Asked Questions
OpenMetadata and DataHub are top community tools with extensible APIs and active support. They offer enterprise-grade features without the cost of commercial solutions.
Collibra, Informatica, and Secoda offer advanced governance, PII tagging, and role-based workflows that meet enterprise compliance requirements.
AI search and auto-tagging can significantly reduce time spent on manual documentation and metadata entry. Secoda, Alation, and Atlan offer leading implementations of AI-powered features.