Soda
Data quality and observability for the modern data stack.
Overview
Soda provides a data quality and observability platform that enables data teams to detect, resolve, and prevent data issues. It uses a declarative language (SodaCL) to define data quality checks, which can be integrated into data pipelines. In a data mesh, domain teams can use Soda to define and enforce quality standards for their data products, ensuring they are fit for consumption.
✨ Key Features
- SodaCL (Checks Language) for defining data quality rules
- Automated data profiling and monitoring
- Anomaly detection
- Incident management and collaboration
- Data lineage integration
🎯 Key Differentiators
- Developer-friendly, checks-as-code approach (SodaCL)
- Strong open-source offering (Soda Core)
- Focus on both data engineers and data consumers
Unique Value: Empowers domain teams in a data mesh to own the quality of their data products by providing a flexible, code-based framework for defining, monitoring, and managing data quality.
🎯 Use Cases (4)
✅ Best For
- Using SodaCL with dbt to test data products before deployment
- Setting up monitors to detect freshness and validity issues
💡 Check With Vendor
Verify these considerations match your specific requirements:
- Data cataloging or business glossary management
- Data access control
🏆 Alternatives
Provides a more comprehensive and collaborative platform for data quality than standalone testing in dbt, and a more code-centric approach than some automated observability tools.
💻 Platforms
🔌 Integrations
🛟 Support Options
- ✓ Email Support
- ✓ Live Chat
- ✓ Dedicated Support (Enterprise tier)
🔒 Compliance & Security
💰 Pricing
✓ 45-day free trial
Free tier: Soda Core is open source. Free trial for cloud platform.
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