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QuerySurge

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25 reviews
  • 1 profiles
  • 3 categories
Average star rating
4.5
Serving customers since
2012

Profile Name

Star Rating

16
9
0
0
0

QuerySurge Reviews

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Profile Name
Star Rating
16
9
0
0
0
Rakshith N.
RN
Rakshith N.
Quality Engineer at Infosys with expertise in Data Engineering and Leading
01/20/2026
Validated Reviewer
Verified Current User
Review source: Organic

Strong ETL Validation Tool with Limited JSON Source Support

I evaluated QuerySurge using the trial version to understand how well it supports real-world ETL and data validation scenarios. From a structured data perspective, QuerySurge is a very solid platform. It provides strong connectivity to a wide range of enterprise systems including databases like Oracle, SQL Server, Snowflake, Teradata, Redshift, and also BI tools such as Power BI, Tableau, Cognos, and SAP Web Intelligence. The interface for building source-to-target comparisons, validations, and reconciliation checks is intuitive and clearly designed for data warehouse and analytics testing teams.
SS
Suleena S.
01/12/2026
Validated Reviewer
Verified Current User
Review source: G2 invite on behalf of seller
Incentivized Review

Powerful Data Testing Made Effortless with QuerySurge

QuerySurge is an extremely powerful automated data testing platform that excels at handling large volumes of data, complex validations, and transformation checks in seconds. It allows us to validate source-to-target data, aggregates, and business rules efficiently, even across very large datasets that would be impractical to test manually. One of the standout features is the AI chat engine, which significantly simplifies test creation. It helps generate query pairs quickly and accurately, reducing the effort required to write and maintain complex SQL. This has been especially helpful for accelerating test development and onboarding new team members. The tool is also easy to use and well accepted by both QA and technical teams. The interface is intuitive, test results are easy to interpret, and the reporting clearly highlights mismatches and failures. Overall, QuerySurge enables faster feedback cycles and increases confidence in data quality across ETL and reporting processes.
Tarun B.
TB
Tarun B.
Associate Test Manager (Data)
12/23/2025
Validated Reviewer
Review source: G2 invite on behalf of seller
Incentivized Review

QuerySurge is a powerful ETL validation tool that enables fast, scalable, and automated data testing across heterogeneous source and target systems.

QuerySurge performs exceptionally well in validating data across heterogeneous databases, even when no direct data bridge exists.

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New York, US

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@QuerySurge

What is QuerySurge?

QuerySurge is an enterprise-grade data testing, validation, and data quality platform designed to ensure trust in data across modern analytics, ETL, and data warehouse environments. QuerySurge automates end-to-end data quality validation by comparing data across heterogeneous sources and targets, including databases, cloud data platforms, jsons and other files, and BI reporting tools. It enables teams to validate completeness, accuracy, consistency, and transformation logic through large-scale source-to-target testing, business rule checks, aggregates, and regression tests, all at production scale. Built-in CI/CD integration, centralized reporting, and role-based dashboards support continuous data quality monitoring as data moves through pipelines and into reports. Ease of use is a core design focus. QuerySurge provides an intuitive interface for building, organizing, and executing tests, with clear visual results that make failures easy to identify and investigate. The Query Wizard provides a guided, step-by-step interface that helps users quickly build data validation tests without needing to write complex SQL from scratch. AI-powered capabilities further simplify test creation by generating tests from mapping documents and allowing users to create or refine SQL using natural language. These features reduce the learning curve, accelerate onboarding, and help both technical and semi-technical users achieve comprehensive data quality coverage faster, with less manual effort.

Details

Year Founded
2012