Continuous Testing with
QuerySurge DevOps for Data
Automate the validation & testing
of your DataOps pipeline
Unlock the Power of DataOps
DevOps revolutionized software delivery by automating development, testing, and operations. Now, the same principles are transforming data workflows.
QuerySurge DevOps for Data brings DevOps automation to data testing, enabling faster, smarter validation at every stage of your pipeline.
Built for Continuous Testing
QuerySurge supports real-time, automated tests triggered by upstream processes. Get immediate feedback on data quality risks before they impact your business.
Why QuerySurge DevOps for Data?
- The industry’s most comprehensive RESTful API
Leverage QuerySurge’s powerful RESTful API to seamlessly integrate data testing into your DevOps pipeline with full control and flexibility. - Extensive API Coverage
With 80+ API calls and hundreds of customizable parameters. - Interactive API Testing
Use our built-in Swagger documentation to explore, test, and validate API calls before using them in production. - Dynamic Test Automation
Programmatically create, execute, and update tests and data stores on demand. - Universal DevOps Integration
Seamlessly connects with virtually any DevOps or CI/CD solution in the market.
DevOps for Data: Core vs. Full API
QuerySurge DevOps for Data comes in 2 versions:
Core API: 5 Base Commands
The Core API is very similar to what our competitors offer.
With the Core API, an external system can securely connect to QuerySurge, provide the appropriate test values, run automated test suites, and retrieve the test status and outcome.
The Core API is free and is included in every package.
Full API: 80+ Commands
The full REST API is the most comprehensive API in the industry.
It lets external tools create, update, run, and monitor QuerySurge tests, connections, suites, and results, automating the complete data-testing process.
The Full API is an add-on module.
Frequently Asked Questions
about DevOps for Data (DataOps)
(To expand the sections below, click on the +)
- How does QuerySurge integrate with CI/CD tools like Jenkins, Azure DevOps, or GitLab?
- Does QuerySurge integrate with ETL/ELT platforms like Informatica, Talend, dbt, or Databricks?
- Does QuerySurge generate audit trails for DataOps processes?
- Can QuerySurge produce compliance-ready reports for regulated industries?
- How does QuerySurge compare to open-source frameworks or homegrown solutions?
- What makes QuerySurge's DevOps for Data different from other solutions in the industry?
- What tools are commonly used for DataOps?
- How do DataOps tools integrate with ETL/ELT platforms?
- What are the best practices for scaling DataOps across an enterprise?
How does QuerySurge integrate with CI/CD tools like Jenkins, Azure DevOps, or GitLab?
Via APIs and webhooks that embed validation directly into CI/CD workflows.
Does QuerySurge integrate with ETL/ELT platforms like Informatica, Talend, dbt, or Databricks?
Yes. QuerySurge works alongside modern ETL/ELT tools to validate their outputs.
Does QuerySurge generate audit trails for DataOps processes?
Yes. Every test run, result, and action is logged.
Can QuerySurge produce compliance-ready reports for regulated industries?
Yes. Reports support regulators such as SOX, HIPAA, GDPR, FedRAMP, FISMA, ISO 9001/ISO 27001, BCBS 239, and CFR Part 11.
How does QuerySurge compare to open-source frameworks or homegrown solutions?
Open-source requires custom code and lacks enterprise features like reporting and CI/CD integration.
What makes QuerySurge's DevOps for Data different from other solutions in the industry?
QuerySurge’s DevOps for Data stands out because it is built around a RESTful API, giving teams direct programmatic control to create, execute, and manage data tests within CI/CD workflows without relying on a command-line interface. It also includes Swagger-powered documentation, so developers can explore endpoints, test API calls, and understand inputs and outputs before integrating them into production pipelines. That makes it easier to embed QuerySurge into tools like Jenkins, Azure DevOps, and other delivery workflows while keeping data validation automated and repeatable. Compared with more generic testing tools, QuerySurge is purpose-built to validate enterprise data across complex pipelines, warehouses, and reporting environments.
What tools are commonly used for DataOps?
ETL/ELT platforms, orchestration tools, monitoring tools, and testing solutions.
How do DataOps tools integrate with ETL/ELT platforms?
They plug into platforms like Informatica, Talend, dbt, and Databricks to enforce data quality gates.
What are the best practices for scaling DataOps across an enterprise?
Standardize pipelines, automate validation, integrate tools, and enforce quality gates across teams.
