Datadog Data Observability review
A Datadog-native view of data quality, lineage, pipeline jobs, and costs.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Datadog Data Observability combines Quality Monitoring and Jobs Monitoring for data and DevOps teams. Quality Monitoring checks lakes and warehouses for freshness, row-count, uniqueness, nullness, schema, and other issues, while machine-learning anomaly detection, custom SQL, GROUP BY monitors, and lineage support investigation. Jobs Monitoring follows failed, delayed, long-running, and costly pipeline jobs. It suits organizations already running Datadog that want data health connected with infrastructure and application telemetry.
The published plans show usage-based pricing, with Quality Monitoring and Jobs Monitoring available separately or together. Quality Monitoring is listed at $24 per monitored table per month on a monthly basis. Jobs Monitoring for Databricks and Apache Spark clusters is $0.05 per host per hour with annual billing or $0.072 per host per hour monthly. Jobs Monitoring for Airflow, dbt, and custom jobs is $0.10 per job per hour annually or $0.144 per job per hour monthly. A 14-day trial is offered, but there is no free plan. Serverless Databricks monitoring is listed as a product option without a displayed price here.
Datadog connects this product with Snowflake, Databricks, BigQuery, Redshift, Apache Spark, Airflow, dbt, and OpenLineage, and the broader platform lists 1,000 integrations. Execution traces can be correlated with logs and data anomalies, while Software Catalog supports incident routing and escalation. OpenLineage support extends monitoring to custom and open-source workloads. Teams invested in Datadog and needing both warehouse checks and pipeline operations should find the combined scope appropriate. Organizations requiring self-hosted deployment, a free tier, or a narrower standalone tool should consider alternatives.
Datadog Data Observability pros and cons
- Where it wins
- Freshness, schema, nullness, uniqueness, and row-count monitoring
- Lineage and anomaly detection connect data issues to downstream impact
- Job traces, cost insights, and alerts span Databricks, Airflow, dbt, and more
- Where it doesn't
- No free plan; access starts with paid usage
- Cloud deployment only, with no self-hosted option listed
- Usage-based pricing requires tracking tables, hosts, and job hours
Datadog Data Observability fact sheet, pricing and score →
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