Metaplane alternatives split into two groups: free or low-cost tools such as OpenMetadata, Soda, and dbt Cloud, and quote-only enterprise platforms such as Monte Carlo, Bigeye, Anomalo, and Datafold. OpenMetadata is free to self-host, Soda has a free tier with a $750 per month Team plan, and dbt Cloud has a free Developer plan with Starter at $100 per user per month. Four of the seven tools publish no price, so a data team should expect a sales conversation and an annual contract for Monte Carlo, Bigeye, Anomalo, and Datafold.
We compared 7 options for metaplane alternatives. Each profile below lists the price, free plan, pros and cons as published by the company.
On this page
Metaplane alternatives: comparison table
Swipe the table sideways on a phone to see every column.
| # | Name | Best for | Starting price | Free plan / trial | Link |
|---|---|---|---|---|---|
| 1 | Monte Carlo | enterprise data observability | quote only | No | Visit |
| 2 | Soda | data contracts and checks | $750 per month | Yes | Visit |
| 3 | Bigeye | data quality monitoring | quote only | No | Visit |
| 4 | Anomalo | ML-based anomaly detection | quote only | No | Visit |
| 5 | Datafold | data diff and CI checks | quote only | No | Visit |
| 6 | OpenMetadata | open-source data catalog and observability | Free | Yes | Visit |
| 7 | dbt Cloud | dbt teams adding observability | $100 per user/month | Yes | Visit |
The 7 best metaplane alternatives, in detail
Monte Carlo
Best for: enterprise data observability
Monte Carlo is the best-known data observability platform, and it suits large data teams that need coverage across warehouses, data lakes, and BI tools. It monitors freshness, volume, schema, and distribution, traces lineage, and manages incidents when a pipeline breaks. The platform works with Snowflake, BigQuery, Databricks, dbt, Looker, and many more, which makes it a fit for a complex stack.
- Pricing is quote-only, with tiers that scale by credits and usage.
- The limits are the tier caps and the sales-led model.
- The Start tier is capped at 10 users, 1,000 monitors, and 10,000 API calls per day, and single sign-on, SCIM, and self-hosted storage need Scale and a
- There is no free plan and no published price, so a team should expect a sales conversation and an annual contract.
Pros
- broad coverage across warehouses, lakes, and BI tools
- strong lineage and incident management
Cons
- Start tier is capped at 10 users, 1,000 monitors, and 10,000 API calls per day
- SSO and SCIM and self-hosted storage are gated to Scale and above
Soda
Best for: data contracts and checks
Soda is a data quality platform built around data contracts and checks written in SodaCL, a simple language that data engineers can version in code. The free tier costs $0 per month and covers basic checks, while the Team plan starts at $750 per month with annual billing and volume discounts available. Soda works with Snowflake, BigQuery, Databricks, Postgres, and more, and it alerts teams in Slack when a check fails.
- The free tier is narrow.
- It is limited to a bundled SPU allotment, with extra SPUs on a pay-as-you-go basis at an unpublished rate, so heavy use can cost more than expected.
- Single sign-on, role-based access, audit logs, and private deployment are gated to Team and above.
- Soda suits a data team that wants checks as code and is willing to pay for the Team plan once the free tier runs out.
Pros
- free tier for getting started
- data contracts and SodaCL checks that data engineers can write as code
Cons
- free tier is limited to a bundled SPU allotment, with extra SPUs on a pay-as-you-go basis at an unpublished rate
- SSO, RBAC, audit logs, and private deployment are gated to Team and above
Bigeye
Best for: data quality monitoring
Bigeye is a data observability platform that automates data quality monitoring, using anomaly detection to flag issues in freshness, volume, and distribution without manual rule writing. It integrates with Snowflake, BigQuery, Databricks, and BI tools, and it offers lineage and root-cause analysis when a metric shifts. The platform suits data teams that want monitoring with less manual setup than a rules-based tool.
- The drawback is access.
- There is no self-serve or free tier, and pricing is opaque and sales-led, with the site routing pricing to a demo request.
- A team cannot try the product or budget for it without talking to sales first.
- Bigeye suits a mid-size or enterprise data team that wants automated monitoring and can work through a sales process, while smaller teams should look
Pros
- automated data quality monitoring with anomaly detection
- integrates with major warehouses and BI tools
Cons
- no self-serve or free tier
- pricing is opaque and sales-led, with the site routing pricing to a demo request
Anomalo
Best for: ML-based anomaly detection
Anomalo is a data quality platform that uses machine learning to learn what normal looks like in your data and flag real anomalies, rather than relying on fixed thresholds. It monitors tables in your warehouse, detects shifts in volume, schema, and distribution, and traces the root cause when a metric moves. The platform suits data teams with large, changing datasets where manual rules would miss subtle issues.
- The limits are cost and time.
- There is no public price or free tier, and pricing is demo-led with an annual contract.
- Checks run as queries in your own warehouse, so the compute lands on your warehouse bill on top of the Anomalo fee.
- The ML model also needs about two weeks to learn your data before it becomes useful.
Pros
- machine learning models that learn normal patterns and flag real anomalies
- strong root-cause analysis
Cons
- no public price or free tier
- checks run as queries in your own warehouse, so compute lands on your warehouse bill
- the ML model needs about 2 weeks to become useful
Datafold
Best for: data diff and CI checks
Datafold is a data reliability platform focused on data diffing, which shows row-level changes in a table before a code change is deployed. It fits dbt CI workflows, where a pull request can show exactly which rows will change, and it covers column-level lineage and data quality checks. The platform suits data teams that deploy often and want to catch breaking changes before they reach production.
- The access model is sales-led.
- There is no free tier and no published price, and pricing is custom and quote-based.
- The open-source data-diff tool was also sunset in 2024, so there is no free entry point left.
- Datafold suits a data team that deploys dbt changes often and can justify a sales-led purchase, while teams that want a free start should look at Soda
Pros
- data diffing that shows row-level changes before a deploy
- strong fit for dbt CI workflows
Cons
- no free tier and no published price
- the open-source data-diff tool was sunset in 2024
OpenMetadata
Best for: open-source data catalog and observability
OpenMetadata is a free, open-source data platform that covers catalog, lineage, and data quality in one place. It is released under Apache 2.0 and costs nothing to self-host, with no licence fee and no user limit. The platform ingests metadata from warehouses, BI tools, and pipelines, and it includes data quality tests, lineage, and collaboration features.
- It suits teams that want a catalog plus observability without a subscription.
- The cost is your own time.
- Self-hosting means you own deployment, upgrades, and infrastructure, including backups and monitoring.
- The managed Collate service is sales-priced, and its free tier reclaims inactive clusters after four weeks.
Pros
- free Apache 2.0 open-source platform with catalog, lineage, and quality checks
- no licence fee
Cons
- self-hosting means you own deployment, upgrades, and infrastructure
- the managed Collate service is sales-priced, and its free tier reclaims inactive clusters after 4 weeks
dbt Cloud
Best for: dbt teams adding observability
dbt Cloud, now sold as the dbt platform, is the managed home for dbt projects, and it is the natural pick for a team that already builds models with dbt. The free Developer plan covers 1 seat, 1 project, and 3,000 successful models built per month, while the Starter plan costs $100 per user per month. The platform covers scheduling, testing, documentation, and orchestration, with lineage and the Semantic Layer on Starter and above.
- The entry limits are tight.
- Developer allows only 1 seat and 1 project, so any real team moves to Starter quickly.
- The Semantic Layer, API access, and lineage are gated to Starter and above, and Enterprise is custom-priced.
- dbt Cloud suits a team that already uses dbt and wants managed scheduling and testing, while teams that need a full catalog should pair it with OpenMe
Pros
- free Developer plan for solo use
- native fit for dbt projects with scheduling, testing, and docs
Cons
- Developer is limited to 1 seat, 1 project, and 3,000 successful models built per month
- Semantic Layer, API access, and lineage are gated to Starter and above
- Enterprise is custom-priced
How we chose
We compared data observability tools that cover the same core job as Metaplane: monitoring data quality, tracing lineage, and alerting teams when a pipeline breaks. We checked each vendor pricing page on 2026-11-12 and used only the figures shown there, writing quote only where no price is published. We favoured tools with a real free tier or trial, a clear starting price, and documentation that explains limits. We did not claim hands-on testing, and we did not use review scores or ratings. Where a vendor gates a feature such as single sign-on or the Semantic Layer to a higher tier, we named the tier so you can budget for it.
Which alternative fits your data team
| Team size and stack | Best pick | Why | | Solo data engineer, $0 budget | OpenMetadata | Free to self-host, catalog plus quality checks | | Small team, checks as code | Soda | Free tier, $750 per month Team plan, SodaCL checks | | dbt team, 2 to 10 people | dbt Cloud | Free Developer plan, Starter at $100 per user per month | | Enterprise, large stack | Monte Carlo | Broad coverage, lineage, incident management | | ML-based detection need | Anomalo | Learns normal patterns, but expect a sales process | | dbt CI and data diffing | Datafold | Row-level diffs before deploy, quote-only | | Automated monitoring, no rules | Bigeye | Anomaly detection, but no self-serve tier |
Frequently asked questions
What is the best free Metaplane alternative?
OpenMetadata is the best free alternative, since it is open source under Apache 2.0 and costs nothing to self-host, with a catalog, lineage, and quality checks included. Soda also has a free tier, and dbt Cloud has a free Developer plan for solo use. OpenMetadata suits a team with engineering capacity that wants full control, while Soda and dbt Cloud suit teams that want a managed service with a free start.
Which Metaplane alternative is best for dbt teams?
dbt Cloud is the best pick for a team that already builds models with dbt, since it offers managed scheduling, testing, and documentation in the same place. Datafold is another strong option for dbt CI, with row-level diffs that show what will change before a deploy. Both cover different jobs, so a dbt team may use dbt Cloud for orchestration and Datafold for diffing, with Soda for checks as code.
Is Monte Carlo better than Metaplane?
Monte Carlo is the largest data observability platform, with broad coverage across warehouses, lakes, and BI tools, plus lineage and incident management. It suits an enterprise data team with a large stack and a budget for a sales-led purchase. Metaplane and smaller tools such as Soda suit teams that want a lower entry price or checks as code. The better choice depends on stack size, budget, and whether you need a managed service or can self-host.
Can I self-host a Metaplane alternative?
Yes. OpenMetadata is free to self-host under Apache 2.0, and it covers catalog, lineage, and quality checks with no licence fee. Soda and dbt Cloud are managed services with free tiers, but they cannot be self-hosted. Self-hosting removes the subscription fee but adds work: you own deployment, upgrades, backups, and monitoring. Compare your team time against the subscription cost before you choose.
How much does it cost to switch from Metaplane?
The direct cost is the new subscription, which ranges from free with OpenMetadata to $750 per month with Soda Team or $100 per user per month with dbt Cloud Starter, plus a quote for Monte Carlo, Bigeye, Anomalo, or Datafold. Migration takes time: recreate monitors and checks, reconnect data sources, and retrain the team on alerts and incident workflows. Expect a few days of work for a small stack, and run both systems side by side during the switch.
Sources
- https://www.montecarlo.ai
- https://www.montecarlo.ai/pricing
- https://www.soda.io
- https://www.soda.io/pricing
- https://www.bigeye.com
- https://www.anomalo.com
- https://www.datafold.com
- https://open-metadata.org
- https://www.getdbt.com
- https://getdbt.com/pricing
Prices and features were read on each company’s own website in November 2026. They change often, so confirm the current offer on the official site before you sign up or buy.