Validata compares source and target across databases and clouds, flags real mismatches, turns them into repair scripts, and re-checks results so modernization, CDC, regulated reporting, and AI all run on the same facts. With Validata, you can drive better:
Operational Reliability
Data Modernization
Regulatory Compliance & Audit Readiness
A four-step validation lifecycle that turns “we think it matches” into “we know it—and can prove it.”
Connect source and target, select tables and key columns, choose a method (full, fast, vector, interval, key, or custom SQL), and set schedules and alerts so the right checks run automatically.
Run jobs on-demand or on a schedule as Validata scans billions of rows across systems, handles in-flight windows, and compares source vs target without overloading databases.
Use one dashboard that classifies every difference, lets you drill to record-level detail, filter by system or table, and track drift trends over time.
Six validation methods tuned to your data’s risk.
Validate massive datasets with vector signatures that reduce network usage for large comparisons.
💡 Efficient for datasets with 100M+ records.
Compare every field in every row when you need exact parity between source and target.
💡 Great for datasets under 10M records.
Use hashes on records to detect mismatches with far less data movement.
💡 Good for datasets with 10M–100M records.
Validate only records in a chosen time window so CDC and streaming checks stay lightweight.
💡 Useful for incremental comparisons.
Check that every key in the source exists in the target so you quickly catch missing or extra records.
💡 Best for spotting missing or extra records.
Run your own SQL on both systems so you can validate aggregates and business rules without extra tooling.
💡 Ideal for specialized comparisons beyond built-in methods.
Keep replicated tables in sync by continuously checking for missing, extra, or changed records before they break dashboards or downstream apps.
Validate legacy-to-cloud moves table by table so architects can cut over, shorten dual-run periods, and decommission systems with evidence.
Schedule recurring checks on financial, healthcare, or other regulated data and retain reports so risk and compliance can show how integrity was verified.
Confirm that feature stores, training sets, and production feeds stay aligned so models don’t drift on quiet data issues.
Use time-window checks on recent events to catch drift in Kafka, logs, and sensor streams without rescanning terabytes of historical data.
Prove that critical tables match across on-prem, Snowflake, BigQuery, Databricks, and more, so leaders know which copy of the truth to trust.
Everything you need to know about Validata.
Validata is an independent, standalone data validation solution that can be used with any data integration tool, including custom-built solutions.
Most data quality tools check rules inside a single system. Validata focuses on source-to-target parity across systems, classifying real mismatches, generating repair scripts, and keeping an audit trail of every validation run.
You could, but you would be rebuilding scheduling, alerting, repair scripts, and history across multiple platforms. Validata standardizes that loop so teams stop maintaining one-off scripts and can reuse the same controls for migrations, CDC, regulated data, and AI.
Validata connects to popular operational databases and modern cloud warehouses, including hybrid and multi-cloud environments, so you can compare legacy sources with platforms like Snowflake, BigQuery, and Databricks from one place.
Validata is designed with performance controls: vector and fast record methods reduce data movement, interval and key validations keep checks lightweight, and you can tune schedules and thresholds so validations run safely alongside production workloads.
No. Validata supports audit readiness by providing evidence of what was validated, what was fixed, and when, but it does not guarantee compliance with any specific regulation.
Teams typically connect a source and target, select a few critical tables, choose validation methods, and get their first reports in a short onboarding window, then expand coverage as they adopt more migrations, pipelines, and models.
Cut incidents in production, keep modernization on track, and trust your AI because you’ve proven source equals target. Contact our experts to learn more.
