I like QuerySurge's structured and user-friendly approach to ETL testing. It simplifies complex data validation tasks and makes it easy to analyze large datasets efficiently. The tool is especially beneficial for beginners, as it clearly demonstrates how data flows through pipelines and how transformations can be validated. Review collected by and hosted on G2.com.

For beginners, the initial learning curve can feel a bit steep, especially when getting familiar with the interface and understanding how to configure connections and parameters properly. Additionally, better documentation and more beginner-friendly examples would be helpful. Review collected by and hosted on G2.com.

The course perfectly bridges the gap between data theory and practice, thanks to the Excel sheets and Word documents provided. Review collected by and hosted on G2.com.

Nothing specific, but the UI could be more interactive and offer easier access for the user. Review collected by and hosted on G2.com.

I like QuerySurge most for its automation capabilities and easy-to-use query pairing framework for ETL validation. I use QuerySurge for ETL and data warehouse testing, which helps automate data reconciliation, perform row-level comparisons, and generate clear test reports. It solves the challenge of validating large volumes of ETL data accurately and efficiently across multiple source and targets. Review collected by and hosted on G2.com.

The UI can feel a bit complex for new users and has a learning curve during initial setup. 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.