Soda

AI-powered data quality monitoring and anomaly detection

Also known as
soda

What is Soda?

An AI-powered data quality platform that automatically detects and helps fix data issues. Core features include metrics monitoring, row-level anomaly detection, and root cause analysis, with failed records automatically stored in your data warehouse.

Independently observed

What Soda does

The capabilities that matter for data observability, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.

Capabilities
Freshness monitoring
-
Volume monitoring
-
Schema change detection
-
Data quality rules
ML anomaly detection
Lineage impact analysis
-
Root cause analysis
Incident management workflow
Dbt native
-
Streaming support
-
Deployment model
Self hosted
Open source
-
Pricing model
-
Independently observed

Platform & deployment

Independently observed
Platforms
  • Web

Integrations (2)

Independently observed
  • Slack
  • Git

Soda alternatives

Other data observability we track, ranked by the same independent score.

All Soda alternatives, ranked →

Compare Soda

Side by side against other data observability, attribute by attribute, with a source on every value.

Independent · unbought · dated

The Vioscale score: one lens on the evidence

Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Soda, not the verdict.

Balanced composite 43 / 100
low · 8%updating
Signal contributions to the composite score
SignalScoreWeightContributionEvidence
Capabilities670.053.3
Integrations140.040.6
Price level00.050.0-
Reliability00.070.0-
Security posture00.070.0-
Pricing transparency00.080.0-

Computed . Re-weight it by intent, or see the full method.

All data & sourcesshow ↓

Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.

Features

AttributeValueEvidence
CapabilitiesDeployment model: self-hosted · Data quality rules: Yes · Root cause analysis: Yes · Ml anomaly detection: Yes · Incident management workflow: Yesmediumsource · 2026-08-21 · 60%

Integrations

AttributeValueEvidence
Count2mediumsource · 2026-08-21 · 60%