QuerySurge Reviews & Product Details

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. Review collected by and hosted on G2.com.

My primary use case, however, involves validating modern data pipelines where the source data is in JSON format, coming from APIs or application systems, and the target is a relational database or data warehouse. This is a very common pattern in today’s data architectures. During my evaluation, I found that QuerySurge does not support JSON files or REST API responses as a native data source. The available source types are mainly limited to databases, BI tools, and flat files like CSV or Excel. Because of this, JSON data must first be transformed and loaded into a database before QuerySurge can be used, which adds extra steps and reduces the effectiveness of true source-to-target validation.

It is not a dislike but its a gap. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

As with most enterprise tools, there is a learning curve at the beginning, particularly for users who are less familiar with SQL or data validation concepts. Some advanced features require deeper product knowledge to use effectively, but once learned, they provide significant value. Review collected by and hosted on G2.com.

1. Helping in validating huge volume of data

2. Ability to validate different kinds of data sources (flat files, excel, databases)

3. Love the Data Staging feature to create temp tables and use them in the main query-pair.

4. Ability to connect to Snowflake and Workday

5. Analyze the errors easily for any data/non-matching errors Review collected by and hosted on G2.com.

Sometimes the agent get hanged abruptly and doesn't allow to kill the running query-pair.

Using multiple Data Staging temporary tables slows down the query-pair execution time.

When using the Data Staging feature, we need to run all the Staging query-pairs before we execute the main-query. Review collected by and hosted on G2.com.

QuerySurge offers support for a broad array of data sources, including databases, flat files, and cloud platforms, which adds to its versatility. Its ability to efficiently manage large datasets is particularly valuable for enterprise-level data warehouses. Review collected by and hosted on G2.com.

The initial setup and configuration can be complex, especially for databases like Snowflake and T24, due to driver compatibility, authentication, and schema intricacies. Additionally, the licensing cost can be a barrier for smaller teams, and the UI can feel sluggish with very large datasets. Review collected by and hosted on G2.com.

I really appreciate how QuerySurge speeds up my testing process and provides accurate results for large volumes of data in less time. It's easy to use, and the report generation feature makes it simple to spot failure counts. I love the feature that allows automatic generation of SQL queries by establishing table-to-table connections. This reduces the time I spend preparing SQL queries, saving a lot of test planning time. The Test Scenario schedule feature is also a favorite because it allows me to complete my validations by scheduling scenarios overnight and then viewing the results the next day. Review collected by and hosted on G2.com.

If we could get the manual for establishing connectivity via JDBC driver for old DBs. Documenting these things would be fine. Like how we can establish connection step by step would be fine. Review collected by and hosted on G2.com.

I used QuerySurge to validate a large volume of records, and it really helps accelerate the testing process and save time in validation of high volume data. QuerySurge allows me to complete my validation efficiently and effectively in a limited time. I really like the QuerySurge staging feature as it helps me validate file vs database comparison. The report generation feature is another highlight for me because it allows me to easily spot the number of data failures in a column for a high volume of data. The initial setup was smooth, and overall, QuerySurge is a lifesaver. Review collected by and hosted on G2.com.

When we have non-matching source and target rows, as well as data failures for a table, the failed record number in the failure tab and the failed number in the report generation seems different, which was bit confusing. Review collected by and hosted on G2.com.

I appreciate how QuerySurge stores query pairs for later use, which allows for flexibility and efficiency in ongoing data comparison tasks. The integration of AI is particularly beneficial, as it eliminates the need to search outside the tool, simplifying workflows and enhancing productivity. By sharing ETL mapping documents, I can generate queries automatically, which saves a significant amount of time and effort. Overall, these features contribute to a seamless and effective experience in handling data-related tasks. Review collected by and hosted on G2.com.

I find that QuerySurge could benefit significantly from generating queries automatically when selecting source and target data points. This would streamline the process and reduce manual work. Additionally, I think it would be advantageous if the QuerySurge team could extend support to address various aspects of data challenges comprehensively. The use of RAG and agents within QuerySurge for automating manual tasks seems like an area that needs more development to enhance functionality and efficiency. Review collected by and hosted on G2.com.

I am very satisfied with QuerySurge, as it serves as our primary tool for file-to-file and database-to-database comparisons. I rely on it to verify results and provide signoffs, and overall, I am happy with its performance. I particularly appreciate the Data Staging options that QuerySurge offers, as they seem to work very well for my needs. Additionally, the initial setup was very easy, making the transition to QuerySurge smooth and hassle-free. Review collected by and hosted on G2.com.

I find the performance of QuerySurge to be a significant challenge, especially when processing large datasets. Executing comparisons on more than 500,000 records can take over 30 minutes, and in the case of 5 million records, it takes roughly an hour. This impacts efficiency and I believe there’s room for improvement in processing speeds. Additionally, the tool doesn't provide detailed record-wise results for past queries, only showing percentages of pass and failure, which limits insight depth. When errors occur due to incorrectly mentioned fields in a query, QuerySurge does not offer specific guidance or suggested modifications, which can hinder troubleshooting efforts. Review collected by and hosted on G2.com.

I find QuerySurge invaluable for QA validation due to its ability to effectively compare large amounts of data. Its user-friendly interface significantly aids in reporting and identifying differences between source and target datasets, making this process more efficient and less error-prone. I appreciate how easy it is to use, getting the job done without unnecessary complications. The software's capability to connect to multiple types of data sources—such as SQL, on-premises, cloud systems, and even using data files—adds tremendous value to its functionality. I also benefit greatly from its own API, which allows for dynamic interactions like changing snippet values and initiating scenarios, making it adaptable and versatile across different use cases. Additionally, its integration with other tools through API requests enhances our workflow, ensuring we can continue to leverage existing systems while making the most of QuerySurge's robust features. Review collected by and hosted on G2.com.

I find the current use of snippets in QuerySurge somewhat static and believe they could be more dynamic. It would be beneficial if snippets had the capability to store queries and other types of code to retrieve values from external sources. This would allow for more flexible use rather than just being a static piece of code or information to be combined within queries or XML. Review collected by and hosted on G2.com.

I really appreciate how QuerySurge facilitates the easy comparison of table data based on query pairs, allowing me to identify differences across various scenarios with efficiency. The ability to store scenarios that can be reused with different data connections is incredibly valuable for our regression suites, as it streamlines the process of running QA tests for each release. Once set up, I can effortlessly trigger these scenarios using specific database connections and have the results ready for review within just 10-20 minutes. Additionally, the capability to export the analysis into Excel is a major advantage, as it enables sharing detailed results with colleagues who might require a deeper dive into the data. Furthermore, the integration with Jenkins script for automating scenario triggers ensures flexible and time-efficient operations, especially for after-hours testing. Although I wasn't part of the initial setup team, my experience with updating QuerySurge to a new version was smooth, indicating the software is user-friendly in terms of maintenance and updates. Review collected by and hosted on G2.com.

Sometimes the analysis in QuerySurge creates false failures, such as when only one column in the table data is different, but multiple columns are highlighted as differences. This leads to confusion and false alerts. Additionally, when data are exactly the same and should match perfectly, they are occasionally incorrectly highlighted as discrepancies. This requires testers to manually scan rows or export data to Excel to apply formulas and verify that no true differences are being overlooked. Review collected by and hosted on G2.com.