Soda vs Bigeye

Soda8.8Visit BBigeye7.4Visit

Higher score Soda #2 in Data Testing Tools 8.8/10 Free plan · paid from $750/mo Free plan✓ 2 of 4 features Visit Soda

vs

B Bigeye #8 in Data Testing Tools 7.4/10 Pricing on request ✓ 3 of 4 features Visit Bigeye

• Soda fits best

  Teams that want quality checks defined simply, starting free, with room to grow into a paid layer

• Bigeye fits best

  Teams that want broad automated metric coverage without defining every check manually

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Side by side

Feature	Soda 8.8/10 Visit ↗	BBigeye 7.4/10 Visit ↗
At a glance
Editor score	8.8	7.4
Ranking	#2 in Data Testing Tools	#8 in Data Testing Tools
Best for	Teams that want quality checks defined simply, starting free, with room to grow into a paid layer	Teams that want broad automated metric coverage without defining every check manually
Pricing model	Free plan + paid	Paid
Starting price	Free plan · paid from $750/mo	Pricing on request
Free plan	✓ (best)	—
Free trial	—	—
Features Soda 2/4 · Bigeye 3/4
Automated anomaly detection	—	✓ (best)
Data lineage mapping	—	—
Alerting integrations	✓	✓
API access	✓	✓
Specs
Deployment model	Hybrid	Cloud
Our review
Pros	Soda Core is genuinely free and open source, with checks written in a short, readable YAML-like syntax Checks map closely to SQL concepts, so analytics engineers pick it up fast without a new query language Soda Cloud adds collaboration, history, and alerting on top of the same checks without rewriting them	Large catalog of pre-built data quality metrics speeds up initial coverage across many tables at once Automated threshold detection reduces the amount of manual rule-tuning needed to get started Built specifically around scaling monitoring across many tables rather than a handful
Cons	Soda Core alone has no hosted dashboard or team collaboration layer — that's the paid upgrade Less automatic anomaly detection out of the box than ML-first observability tools on this list Checks still have to be written per table or dataset; it won't discover what to check on its own	What it costs stays unclear until sales gets involved; nothing is listed publicly Less governance/catalog depth than platforms built around stewardship workflows Pre-built metrics still need review to make sure they match what actually matters for a specific dataset
Our verdict	Soda's pitch is that quality checks shouldn't need a new mental model: its check syntax reads close enough to SQL that an analytics engineer can write "row count > 0" or "missing_count(column) = 0" and move on, instead of learning a… Read the review →	Bigeye's approach is to front-load a large catalog of pre-built metrics so a team gets broad coverage across many tables quickly, instead of hand-writing a check for each one before monitoring starts. Automated threshold detection on top… Read the review →

Strengths and trade-offs

• Soda — where it wins

  • Soda Core is genuinely free and open source, with checks written in a short, readable YAML-like syntax
  • Checks map closely to SQL concepts, so analytics engineers pick it up fast without a new query language
  • Soda Cloud adds collaboration, history, and alerting on top of the same checks without rewriting them

  Where it doesn't

  • Soda Core alone has no hosted dashboard or team collaboration layer — that's the paid upgrade
  • Less automatic anomaly detection out of the box than ML-first observability tools on this list
  • Checks still have to be written per table or dataset; it won't discover what to check on its own

• Bigeye — where it wins

  • Large catalog of pre-built data quality metrics speeds up initial coverage across many tables at once
  • Automated threshold detection reduces the amount of manual rule-tuning needed to get started
  • Built specifically around scaling monitoring across many tables rather than a handful

  Where it doesn't

  • What it costs stays unclear until sales gets involved; nothing is listed publicly
  • Less governance/catalog depth than platforms built around stewardship workflows
  • Pre-built metrics still need review to make sure they match what actually matters for a specific dataset

• Soda8.8/10 · Free plan · paid from $750/mo

  Checks are plain SQL-adjacent config, approachable for teams who aren't buying a platform yet.

  Visit SodaFull verdict →
• BBigeye7.4/10 · Pricing on request

  Leans on a large library of pre-built metrics so a team isn't writing every check from scratch.

  Visit BigeyeFull verdict →