Lightup

Founded by Manu Bansal

Monitor and validate enterprise data pipelines continuously with automated anomaly detection

Pricing model

Demo, Paid

Rating

★ Positive

Time to value

> 4 Hours

You can use Lightup to monitor and validate production data pipelines across your warehouse without moving any records. It pushes SQL queries directly to your data stores like Databricks, Snowflake, or cloud object storage to detect discrepancies and anomalies automatically. Using prebuilt machine learning checks, it catches missing values, drift, and broken data contracts without requiring manual rule configuration. You can also interact with monitoring systems using coding assistants like Claude or Gemini to investigate incidents, track lineage, and automate remediation workflows across enterprise operations.

What Lightup does

Run pushdown data quality queries directly inside warehousesTrack data pipeline schema changes automaticallyDetect metric and volume anomalies using machine learningInvestigate pipeline errors using agentic prompts in Claude or GeminiInspect data lineage to evaluate downstream disruptionTrigger incident alerts to PagerDuty during pipeline failuresAudit unstructured and streaming records for inconsistenciesPushdown query architecture that executes data checks inside your warehouse without exporting dataPrebuilt machine learning models that detect anomalies without manual threshold configurationAgentic interface compatible with Claude and Gemini for managing checks through natural languageFull data reconciliation and schema drift detection across cloud object storage and databasesNative support for streaming data validation through ksqlDB connectorsIntegrated data lineage mapping for root-cause and downstream impact analysisReal-time incident alert routing to systems like PagerDuty

Pricing breakdown

Pricing model: Book a demo

Frequently asked

Databricks Dremio

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