At a glance
| Supported data platforms | PostgreSQL, Snowflake, BigQuery, Databricks, DuckDB, Redshift, Athena, SQL Server, Fabric, Synapse, Trino, Spark DataFrames |
| Anomaly detection | Metrics monitoring and record-level anomaly detection in Soda Cloud |
| Freshness and volume monitoring | Metrics observability in Soda Cloud, included from the Free plan |
| Schema checks | Yes, contracts validate schema |
| Validation rules | 50+ built-in checks in YAML data contracts |
| Lineage and root cause | Lineage and impact, record-level diagnostics (Cloud) |
| Alerting | Alerting and ticketing integrations (Cloud) |
| Deployment | Soda Cloud SaaS, self-hosted Soda Core, Soda Runner, private deployment on Team |
| Licensing | Core: Elastic License 2.0; Cloud: Free, Team $750 per month, Enterprise custom |
Soda suits engineering-led teams that want data quality checks as code in their pipelines, with a published price ladder: a free plan, then $750 per month for Team. Note the licence change: Soda Core is now under the Elastic License 2.0, fine for internal use but no longer Apache 2.0 open source, which matters if your policy requires an OSI licence.
Overview
Soda Core is a data quality and data contract verification engine. In version 4 you describe a dataset's expected schema and quality checks as a contract in YAML, then generate, test, publish and verify contracts with the CLI or Python API, locally, in a pipeline or remotely through Soda Cloud. The README cites more than 50 built-in checks, and each data source has its own package (soda-postgres, soda-snowflake and so on). Version 3, with the older SodaCL check language, is now legacy.
Soda Cloud is the hosted platform: it stores contracts and results, provides metrics monitoring with anomaly detection, record-level anomaly detection, a diagnostics warehouse that keeps failed records in your own warehouse, lineage and impact views, alerting and a no-code interface for business users. A Soda Runner (formerly Soda Agent) can execute verifications inside your environment. In 2026 Soda changed the Core licence to the Elastic License 2.0.
Key features
- Data contracts in YAML verified by the Soda Core CLI or Python API
- More than 50 built-in data quality checks, plus schema validation
- Metrics monitoring with anomaly detection and record-level anomaly detection (Soda Cloud)
- Diagnostics warehouse that stores failed records in your own warehouse
- Soda Runner (formerly Soda Agent) to run verifications in your environment
- Alerting, ticketing and catalog integrations; Soda MCP for AI agents
- Collaborative contract authoring with a no-code interface for business users (Team plan)
Integrations and ecosystem
Pros and cons
Pros
- Published entry prices: free plan and a $750 per month Team plan
- Checks as code in YAML, runnable in any pipeline from the CLI or Python
- Free Core engine for internal and production use
- Failed records stay in your own warehouse
Cons
- Soda Core is no longer OSI open source (Elastic License 2.0 since 2026)
- Free plan SPU allowance and dataset limits are not stated on the pricing page
- Anomaly detection and collaboration need Soda Cloud
- Version 4 contracts replace the version 3 SodaCL approach, so older examples need migration
Pricing
Soda's pricing page lists Free at $0 per month (unlimited users, pipeline testing, metrics observability, alerting and a free allowance of Soda Processing Units, with extra SPUs pay as you go), Team at $750 per month (data contracts, no-code interface, AI features, audit logs, RBAC, SSO, private deployment, premium support; annual billing and volume discounts available) and Enterprise at custom pricing. The page shows a $ sign without naming the currency and does not state the free SPU amount. The Soda Core README separately describes a free account for up to three datasets, which the pricing page does not mention. Soda Core itself is free to use under the Elastic License 2.0.
Pricing checked on the vendor's official page on 7 November 2026. Prices change; confirm before buying.
Who it is best for
Data engineering teams that want code-first data contracts in their pipelines, with an affordable hosted tier for monitoring and collaboration.
Typical use cases
- Fail an Airflow or dbt pipeline step when a dataset breaks its data contract
- Agree a data contract between a producing team and analytics consumers
- Monitor key business metrics for anomalies in Soda Cloud
- Keep failed records in Snowflake or Databricks for investigation
Who should look elsewhere
- Teams that require an Apache 2.0 or other OSI-licensed engine: see GX Core.
- Teams wanting fully automated warehouse-wide monitoring without writing contracts: see Monte Carlo.
Verdict
Soda offers one of the clearest price ladders in data quality and a capable contracts engine you can run anywhere. The 2026 move to the Elastic License 2.0 is the key caveat for teams that need true open source, while most internal users will be unaffected.
Frequently asked questions
Is Soda Core open source?
Not in the OSI sense any more. Soda moved Soda Core from Apache 2.0 to the Elastic License 2.0 in 2026. You can still use, modify and run it in production for free, but you may not offer it to others as a managed service.
How much does Soda Cloud cost?
The pricing page lists Free at $0 per month, Team at $750 per month (annual billing and volume discounts available) and Enterprise at custom pricing. Extra Soda Processing Units are pay as you go.
What is the difference between Soda Core and Soda Cloud?
Soda Core is the engine that verifies YAML data contracts from a CLI or Python. Soda Cloud is the hosted platform that adds central management, anomaly detection, lineage, record-level diagnostics, alerting and a no-code interface.
Does Soda still use SodaCL?
SodaCL checks belong to Soda Core version 3, which the repository now calls legacy. Version 4 is built around data contracts.
Sources
- Soda pricing
- Soda Core GitHub repository
- Soda Core LICENSE (Elastic License 2.0)
- Soda Core licence update: moving to Elastic License 2.0
- soda-core on PyPI
- Soda home page
Checked November 2026.
Listed in: Data Quality & Observability.
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