Metaplane vs Soda: Complete Comparison for 2025
Metaplane offers automated ML-powered monitoring. Soda gives you explicit control with SodaCL. Here's how to choose between them for your data team.
Choose Metaplane if you want:
- ✓Automated detection without writing checks
- ✓Same-day setup with minimal configuration
- ✓ML-powered anomaly detection out of the box
- ✓Built-in data lineage
- ✓Managed SaaS (no infrastructure)
Choose Soda if you want:
- ✓Explicit, version-controlled data quality rules
- ✓Open-source option (Soda Core is free)
- ✓Tight dbt pipeline integration
- ✓Self-hosted deployment option
- ✓Fine-grained control over every check
Feature-by-Feature Comparison
| Feature | Metaplane | Soda |
|---|---|---|
| Primary Approach | ML-powered automated monitoring | YAML-based check definitions |
| Best For | Teams wanting automated detection | Teams wanting explicit test definitions |
| Pricing Model | Contact sales | Free core + paid cloud |
| Setup Time | Same day | Days (requires writing checks) |
| Anomaly Detection | ML-powered (automatic) | Manual thresholds + Soda Cloud ML |
| Schema Monitoring | Yes (automatic) | Yes (via checks) |
| Freshness Monitoring | Yes (automatic) | Yes (via checks) |
| Custom Validation | SQL-based rules | SodaCL language |
| dbt Integration | Yes | Yes (strong) |
| Data Lineage | Yes | Basic (Soda Cloud) |
| Open Source Option | No | Yes (Soda Core) |
| Infrastructure Needs | SaaS only | Self-hosted or SaaS |
| Learning Curve | Low (mostly automated) | Medium (need to learn SodaCL) |
| Snowflake Support | Yes | Yes |
| BigQuery Support | Yes | Yes |
| PostgreSQL Support | Yes | Yes |
Deep Dive: Key Differences
Approach to Data Quality
Metaplane takes an automated, ML-first approach. Connect your data warehouse and Metaplane automatically learns patterns in your data—detecting anomalies, freshness issues, and schema changes without you writing rules. This is great for teams that want comprehensive coverage quickly.
Soda uses an explicit, rule-based approach with their SodaCL language. You write YAML checks that define exactly what you want to test. This gives you complete control but requires upfront investment in defining your expectations.
Example Soda check:
checks for orders:
- row_count > 0
- freshness(created_at) < 1d
- missing_percent(customer_id) < 5%
- duplicate_count(order_id) = 0Pricing and Accessibility
Soda has a significant advantage here: Soda Core is completely free and open-source. You can run data quality checks in production without paying anything, though you'll need to build your own alerting and dashboards. Soda Cloud adds these features for a fee.
Metaplane is a commercial product with contact-sales pricing. There's no free tier, which may be a barrier for small teams or those wanting to experiment. However, their pricing is generally more accessible than enterprise tools like Monte Carlo.
dbt Integration
Both tools integrate with dbt, but Soda has an edge for dbt-centric workflows. Soda checks can be embedded directly in your dbt project and run as part of your dbt pipeline. The YAML-based configuration fits naturally with dbt's approach.
Metaplane integrates with dbt metadata and can track dbt model changes, but operates more as an external monitoring layer rather than embedded in your dbt workflow.
When Each Tool Shines
Metaplane excels when:
- • You want monitoring running today, not next month
- • You don't have bandwidth to write and maintain checks
- • You need data lineage capabilities
- • Your team prefers a managed SaaS solution
- • You want to catch unknown unknowns via ML
Soda excels when:
- • Budget is a primary constraint (Soda Core is free)
- • You want version-controlled, explicit test definitions
- • dbt is central to your data stack
- • You need self-hosted deployment
- • Your team prefers code-first approaches
Frequently Asked Questions
What is the difference between Metaplane and Soda?
Metaplane uses ML-powered automated monitoring that detects anomalies without manual configuration. Soda uses a YAML-based approach (SodaCL) where you explicitly define data quality checks. Metaplane is faster to set up but less customizable; Soda requires more initial work but offers more control.
Is Soda or Metaplane better for small teams?
For small teams wanting quick setup with minimal configuration, Metaplane is often better. For teams with engineering capacity who want fine-grained control over their data quality rules, Soda (especially the free Soda Core) may be preferable. Consider your team's bandwidth and budget.
Can I use Soda for free?
Yes, Soda Core is open-source and free to use. It provides the core check functionality via SodaCL. Advanced features like ML-powered anomaly detection, collaboration, and a hosted dashboard require Soda Cloud, which is paid.
Which tool has better dbt integration?
Both integrate well with dbt, but Soda has a slight edge for dbt-centric workflows. Soda checks can run directly in dbt pipelines, and their YAML-based approach fits dbt's philosophy. Metaplane offers strong integration but operates more as an external monitoring layer.
Looking for a Third Option?
Sparvi combines automated monitoring with startup-friendly pricing. Built specifically for small data teams of 3-15 people who need enterprise-grade observability without the enterprise complexity.