# Metaplane

> Data quality monitoring and incident detection for data warehouses

- **Canonical URI:** https://www.vioscale.ai/software/metaplane
- **Category:** Data Quality
- **Homepage:** https://www.metaplane.dev
- **Also known as:** metaplane
- **Profile claimed by vendor:** no
- **Last updated:** 2026-08-25T08:44:31.871Z

## Vioscale score

**79.3 / 100**, confidence 55% (medium). Computed 2026-09-01.

Composite of weighted, independently-sourced signals (no user reviews, no vendor payment).

| Signal | Score | Weight | Contribution | Evidence present |
|---|--:|--:|--:|:--:|
| price_level | 80 | 0.052 | 4.2 | ✓ |
| reliability | 0 | 0.073 | 0 | - |
| capabilities | 100 | 0.04877777777777778 | 4.9 | ✓ |
| integrations | 41.6 | 0.04066666666666666 | 1.7 | ✓ |
| security_posture | 85 | 0.073 | 6.2 | ✓ |
| pricing_transparency | 80 | 0.084 | 6.7 | ✓ |

## Pricing

_As of 2026-08-25, [verify at source](https://www.metaplane.dev/pricing). Independently observed._

Hybrid · Free tier · 14-day trial

> Free plan with 10 tables, then pay per monitored table for Pro, or custom Enterprise pricing

| Plan | Price | Free | Commitment |
|---|---|:--:|---|
| Free | Free | ✓ | - |
| Pro | Pay per monitored table + $12/user/month | - | - |
| Enterprise | Contact sales | - | - |

### Free

Free forever plan with basic monitoring

**Included limits:** users: 4, monitored_tables: 10, custom_sql_monitors: 3

- 10 monitored tables
- 4 users
- Unlimited viewers
- Volume, schema, freshness, uniqueness, nullness, statistical distribution monitoring
- Manual thresholds
- Basic alerting to Slack, Email, MS Teams
- Email support

### Pro

Usage-based pricing for growing data teams

**Included limits:** users: 12, monitored_tables: 100, custom_sql_monitors: 5

- Everything in Free
- 100 monitored tables
- 12 users
- Unlimited viewers
- Column-level lineage
- Data pipeline visibility
- Data CI/CD with regression testing
- Cost & performance monitoring
- Data usage insights
- dbt job monitoring
- Query monitoring
- Custom SQL monitors
- Alerting to Slack, Email, MS Teams, PagerDuty
- Premium support, shared Slack channel, CSM

### Enterprise (Contact sales)

Custom pricing for enterprise-grade teams

**Included limits:** users: Custom, monitored_tables: Unlimited, custom_sql_monitors: 5

- Everything in Pro
- Unlimited monitored tables
- Custom user limits
- Automated anomaly detection with ML
- Advanced monitor types (partition, rolling window)
- Data impact previews
- Data test previews
- Warehouse spend monitoring
- Custom SQL monitors with ML models
- Custom integrations
- SSO (Okta, AD, SAML)
- AWS or Azure PrivateLink support
- Alerting to Slack, Email, MS Teams, PagerDuty, API, Webhooks
- Model adjustment based on user feedback
- Premium support, shared Slack channel, dedicated CSM, engineering time

### Add-ons

- **Data Impact Previews**
- **Data Test Previews**
- **Warehouse Spend Monitoring**
- **Credit and Spend Monitoring**

## About

A data observability platform that monitors data warehouse quality using automated alerts, detects anomalies, and traces column-level lineage from source to analytics tools to help data teams identify and resolve data quality issues quickly.

_Independently observed._

## Platform & deployment

- **Platforms:** Web
- **Deployment:** Cloud / SaaS, Self-hosted

## Integrations (27)

_Independently observed._

- Snowflake
- BigQuery
- Redshift
- Clickhouse
- Postgres
- MySQL
- SQL Server
- Databricks
- dbt
- Fivetran
- Looker
- Tableau
- Metabase
- Mode
- Sigma
- PowerBI
- Slack
- MS Teams
- PagerDuty
- API
- Webhooks
- GitHub
- GitLab
- Jira
- Segment
- Hex
- Email

## Capabilities

_The capabilities that matter for Data Quality. "-" = undocumented, not absent._

| Capability | Supported |
|---|:--:|
| **Capabilities** | |
| Deployment model | Cloud managed saas |
| ML automated anomaly detection | ✓ |
| Custom python sql testing rules | ✓ |
| Column level data lineage tracing | ✓ |
| Data freshness delay monitoring | ✓ |
| Schema change drift alerts | ✓ |
| Data volume anomaly monitoring | ✓ |
| Snowflake bigquery dwh sync | ✓ |
| Dbt airflow orchestration sync | ✗ |
| Slack pagerduty incident routing | ✓ |
| SOC2 type ii | ✓ |
| ISO 27001 | ✓ |
| Pricing model | Data volume compute tier |

## Facts

Every value below carries its source and our confidence. Facts are re-crawled on a freshness schedule.

### pricing

| Attribute | Value | Source | Retrieved | Confidence |
|---|---|---|---|---|
| pricing.free_tier | yes | [link](https://www.metaplane.dev/pricing) | 2026-08-25 | 60% (medium) |
| pricing.model | freemium | [link](https://www.metaplane.dev/pricing) | 2026-08-25 | 60% (medium) |
| pricing.price_level | low | [link](https://www.metaplane.dev/pricing) | 2026-08-25 | 60% (medium) |
| pricing.transparent | yes | [link](https://www.metaplane.dev/pricing) | 2026-08-25 | 60% (medium) |

### security

| Attribute | Value | Source | Retrieved | Confidence |
|---|---|---|---|---|
| security.soc2 | yes | [link](https://www.metaplane.dev/security) | 2026-08-25 | 75% (high) |
| security.disclosure_policy | yes | [link](https://www.metaplane.dev/pricing) | 2026-08-25 | 60% (medium) |
| security.gdpr | yes | [link](https://www.metaplane.dev/security) | 2026-08-25 | 75% (high) |
| security.hipaa | yes | [link](https://www.metaplane.dev/security) | 2026-08-25 | 75% (high) |
| security.iso27001 | yes | [link](https://www.metaplane.dev/security) | 2026-08-25 | 75% (high) |

### integrations

| Attribute | Value | Source | Retrieved | Confidence |
|---|---|---|---|---|
| integrations.count | 27 | [link](https://www.metaplane.dev/pricing) | 2026-08-25 | 60% (medium) |

### market

| Attribute | Value | Source | Retrieved | Confidence |
|---|---|---|---|---|
| market.availability | `{"primaryMarkets":[],"availabilityScope":"global","availableCountries":[],"notAvailableCountries":[]}` | [link](https://www.metaplane.dev/pricing) | 2026-08-25 | 75% (high) |

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*Source: Vioscale (https://www.vioscale.ai/software/metaplane). Independent, evidence-based software intelligence. Cite the canonical URI.*