Flags risky joins, null filters, hardcoded dates, and metric logic in pull requests.
Production reliability for dbt teams
Trust your data pipelines in production.
Relium reviews SQL and dbt pull requests, traces downstream impact, and alerts your team before bad data reaches dashboards.
Built for teams running production dbt pipelines.
Data pipeline
Relium lives in the transformation layer, before bad logic ships.
Most data tools watch jobs after they run. Relium reviews the dbt and SQL change before production, traces what it can affect, and sends the team a clear risk narrative.
Relium sits here
Risk caught
Review Layer
Relium
SQL risk, dbt lineage, RCA, and team alerts before production deploys.
What Relium does
Turns a risky PR into an actionable data incident preview.
Relium combines code review, lineage, metadata, and team alerts so reviewers know what changed, what breaks, who is affected, and what to fix.
Shows which downstream models, metrics, dashboards, and reports may be affected.
Summarizes likely cause, impacted assets, confidence, and suggested next action.
Problem
Your pipeline can pass. Your metrics can still be wrong.
Production analytics break most often in quiet ways: a review misses a risky SQL change, lineage impact is unclear, and dashboards keep loading with corrupted numbers.
Risky SQL changes
Catch joins, filters, schema assumptions, and metric logic that look harmless in a diff but change business results.
Silent dashboard corruption
Spot downstream risk before bad numbers arrive in dashboards, board reports, or operating reviews.
Manual review gaps
Give reviewers context about affected models, metrics, and owners without asking them to reconstruct lineage by hand.
Real-time incidents
Relium turns production anomalies into clear incident previews.
Short root-cause narratives, affected assets, and recommended action before a data issue becomes a boardroom question.
Null Spike
- Root Event
- Null rate jumped 8x
- Root Table
- stg_payments
- Affected Models
- 12
- Primary Hypothesis
- Upstream API stopped sending payment_method.
- Recommended Action
- Quarantine latest batch and notify Finance owner.
Duplicate Ingestion
- Root Event
- Primary keys duplicated
- Root Table
- raw_orders
- Affected Models
- 9
- Primary Hypothesis
- Retry job replayed a completed load window.
- Recommended Action
- Deduplicate by load_id and pause downstream marts.
Freshness Failure
- Root Event
- Table stale by 3h
- Root Table
- events_sessionized
- Affected Models
- 18
- Primary Hypothesis
- Orchestrator skipped the hourly session job.
- Recommended Action
- Backfill current window before KPI refresh.
Data Loss
- Root Event
- Rows dropped 42%
- Root Table
- fct_revenue_daily
- Affected Models
- 31
- Primary Hypothesis
- Filtered join removed customers without orders.
- Recommended Action
- Block release and restore last trusted model.
Built for production dbt teams
Fits into the workflow your data team already uses.
dbtModel-aware review using manifest and lineage context.
GitHubPull request checks with impact summaries before merge.
SlackAlerts for owners when risky changes touch business metrics.
CI/CDReliability gate that fits into existing release workflows.
Warehouse metadataFreshness, schema, and aggregate signals without raw records.
Production analytics deserve a preflight check