Metaplane.
Founded 2019 · Boston, MA
Status · ● acquired
ML-powered, no-code data observability for the dbt and warehouse stack with automatic column-level lineage — now Metaplane by Datadog.
Where it fits — and where it doesn't.
Startups and scaleups on a Snowflake, BigQuery, Redshift, or Databricks plus dbt stack that want fast, low-effort ML-based monitoring — roughly fifteen-minute setup, useful alerts within days — and want to pay only for the tables they actually monitor. Strong for analytics-engineering teams that want anomaly detection, automatic column-level lineage, and PR-time Data CI/CD checks without standing up a heavyweight enterprise platform.
You need a catalog or governance layer — Metaplane is observability, not catalog: no business glossary, no access workflows, no PII auto-classification. Reconsider too if you want vendor-neutral metadata portability, since there is no OpenLineage support and lineage is proprietary. Acquired by Datadog (April 2025); expected to fold into the Datadog platform over time — roadmap independence is uncertain.
The honest scorecard.
- ML anomaly detection that accounts for seasonality and trend, with very fast time-to-value (about fifteen-minute setup, alerts within days)
- Automatic end-to-end column-level lineage across warehouse, dbt, ingestion (Fivetran/Airbyte) and BI tools, with no manual instrumentation
- A genuine free-forever tier (10 monitored tables) and usage-based "pay only for monitored tables" pricing, payable with Snowflake credits via the Snowflake-native app
- Data CI/CD — regression and impact tests on GitHub/GitLab pull requests for dbt Core and Cloud, shifting checks left
- Backing and continuity from Datadog post-acquisition, with metadata-only read access (SOC 2 Type II, GDPR, HIPAA)
- Roadmap and independence risk — acquired by Datadog in April 2025 and expected to be folded into the Datadog platform over time
- No OpenLineage support and a proprietary lineage model, so metadata is locked into Metaplane
- Not a catalog or governance tool — no business glossary, access workflows, or PII auto-classification
- Paid pricing is published only as "usage-based / pay per monitored table" with no dollar figure; real cost requires a quote
- Lighter incident management and no production circuit breaker compared with heavier platforms like Monte Carlo
What Metaplane actually is.
What Metaplane is
Metaplane is a SaaS data observability platform that connects to a cloud warehouse and uses machine-learning anomaly detection to monitor freshness, volume, schema, nullness, uniqueness, and distribution — with no-code monitor setup and automatic column-level lineage across the modern data stack. On top of production monitoring it offers Data CI/CD: regression and impact checks that run on pull requests for both dbt Core and dbt Cloud. Founded in Boston in 2019 (Y Combinator), it raised roughly USD 22M before being acquired by Datadog in April 2025, and now operates as “Metaplane by Datadog.”
Where it fits
Metaplane sits between the lightweight, in-project approach of elementary and the heavyweight enterprise platforms monte-carlo and bigeye. Against Elementary it is a hosted, ML-first, no-code product that also covers ingestion and BI, not just the dbt project. Against Monte Carlo, Bigeye, and anomalo it is cheaper, faster to deploy, and aimed at smaller teams — trading depth of incident workflow for simplicity. Against datafold, both run PR-time checks, but Datafold leads on value-level data diffing while Metaplane leads on production ML monitoring.
On the Datadog acquisition
Datadog announced the acquisition on 23 April 2025. As of mid-2026 the product still ships standalone as “Metaplane by Datadog,” with features and support intact, and Datadog has stated it will bring Metaplane’s capabilities into the broader Datadog platform over time. The product ships standalone today with support intact. The risk is the multi-year horizon — Datadog has said it will fold Metaplane into the broader platform, so confirm standalone pricing and roadmap if a guaranteed point tool matters.
How to evaluate it
Connect the free tier to your warehouse, let the ML monitors learn for a week or two, and judge two things: signal quality (are the anomaly alerts actionable, or noisy on seasonal data?) and lineage usefulness (does the automatic column-level graph reach across dbt, ingestion, and your BI tool?). If you ship dbt changes through pull requests, wire up Data CI/CD and see whether the impact previews catch a regression before merge.
All capabilities by cluster.
Quality & testing
Primary · strength 3/3Lineage & metadata
Secondary · strength 2/3Where it plugs in.
Native warehouse support
The honest pricing breakdown.
Free tier Free-forever plan covers 10 monitored tables, automated anomaly detection, column-level lineage, 3 custom SQL monitors, and Slack/Email/Teams alerts. A 14-day full-feature trial is offered on signup.
Sales-only tier Pro is usage-based (pay per monitored table, no public dollar figure); Enterprise is custom
What it doesn't do.
Emits and consumes OpenLineage events as a first-class citizen rather than via a plugin or adapter. Signals commitment to interoperability with other metadata tooling — Marquez, OpenMetadata, Astronomer, and others can consume the same event stream. Increasingly the differentiator between "open" and "proprietary metadata model" observability platforms.
Business Glossary →A managed vocabulary of business terms ("Active Customer", "Recognized Revenue") with definitions, owners, and — critically — links to the physical assets that implement them. Without the linking layer a glossary is just a wiki. With it, you can answer "which dashboards use our official definition of Active Customer?" — the question governance teams actually care about.
Data Contracts →Explicit, versioned agreements between data producers and consumers specifying schema, semantics, SLAs, and breaking-change policy. Enforced in CI for producers and at consumption time for consumers. Distinct from schema validation alone — a contract captures intent, not just structure. Implementations vary wildly; many tools claiming "data contracts" offer only schema checks.
Circuit Breaker →Halts downstream execution when a test fails — preventing bad data from propagating into marts, ML features, or BI dashboards. Requires tight integration with the orchestrator (Airflow, Dagster, dbt Cloud). Distinct from alerting-only tools which notify after damage is done.
Drill into one capability.
Other key features
If not Metaplane, then what?
Common alternatives
Quick answers.
- Is Metaplane open source?
- No. Metaplane is a proprietary product, though it offers a free tier.
- How much does Metaplane cost?
- Metaplane publishes pricing on its site. A free tier is available: Free-forever plan covers 10 monitored tables, automated anomaly detection, column-level lineage, 3 custom SQL monitors, and Slack/Email/Teams alerts. A 14-day full-feature trial is offered on signup.
- How is Metaplane deployed?
- Metaplane is a managed cloud (SaaS) product.
- Does Metaplane work with dbt and my warehouse?
- It has a native dbt integration. Metaplane supports snowflake, bigquery, redshift, databricks, postgres, plus 3 more.
More quality & testing tools
Provenance.
Last verified 2026·05·30 against vendor documentation and, where possible, hands-on trial. Spot something off? Send a correction →