Software testing database tutorials and videos

AI-Driven Test Automation for AWS Glue ETL Pipelines: A Practical Framework for Catching Schema Drift and Hidden Data Quality Issues

Software Testing Magazine — Mon, 05 Jan 2026 16:11:35 +0000

Anyone who has spent time working on cloud ETL pipelines knows that the biggest problems aren’t the ones that cause your jobs to fail, they’re the quiet ones that slip through unnoticed. AWS Glue is a powerful tool, but it doesn’t tell you when your data is subtly wrong. In this article, I walk through a validation approach I’ve built and refined over the years, combining practical QA techniques with lightweight AI to detect tricky issues like schema drift, misaligned fixed-length records, and odd shifts in how the data behaves over time. Everything here comes from real projects in healthcare and large enterprise environments where data quality matters a lot more than a green “SUCCESS” message in the logs. Authors: Srikanth Kavuri, Senior Software QA Automation Engineer (AI-Driven Healthcare and cloud based Systems), https://www.linkedin.com/in/srikanth-kavuri-0937b9132/ 1. Introduction If you’ve ever been responsible for validating an ETL pipeline, you’ve likely felt that uneasy moment when everything “looks fine,” yet something in your gut says, “Something is off.” I’ve had jobs in AWS Glue that ran cleanly from start to finish, only for a downstream report to blow up the next morning because someone upstream changed a field or shifted the way a fixed-length file was formatted. And this is the real problem Glue handles transformations, but it doesn’t verify the correctness of the data. Many teams assume it does, and that leads to silent data corruption. This article lays out an approach that testers and engineers can use to guard against these [...]

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Open Source Database Testing Tools

Software Testing Magazine — Thu, 26 Sep 2024 08:00:55 +0000

Database testing is one of the areas that might have the smaller number of open source tools. The programming languages have many xUnit tools and mocking frameworks, but this is not the case for databases. This article provides a list of open source tools that can be used to perform unit, load and security testing on several relational (MySQL, Oracle, SQLServer, etc.) and NoSQL databases. This situation might be the results of the fact that most of the main relational databases are commercial tools that come with an infrastructure already provided by the vendors. The current rise of the NoSQL databases and the many forks that have been created from the original MySQL open source relational database might however change this situation in the future. The tools covered in this article are Database Benchmark, Database Rider, DBChaos, DBKover, dbstress, DbUnit, DB Test Driven, GODBT, HammerDB, JdbcSlim, JdbcRunner, JDBDT (Java DataBase Delta Testing), Mindleaf, MyTAP, NBi, NoSQLMap, NoSQLUnit, pgTAP, pstress, ruby-plsql-spec, SeLite, simple-db-tester, Spring DBUnit, SQLancer, sqlmap, tSQLt, Tsung, TypeORM Seeding, utPLSQL. Updates September 26 2024; added DBChaos, SQLancer, TypeORM Seeding February 14 2023: added DBKover, GODBT, pstress, simple-db-tester May 5 2020: added JdbcRunner, Mindleaf, MyTAP, pgTAP, Spring DBUnit January 23 2017: added JDBDT (Java DataBase Delta Testing), Database Rider, dbstress, NBi July 18 2016: added JdbcSlim, ruby-plsql-spec, Tsung, utPLSQL December 1 2016: added SeLite Database Benchmark Database Benchmark is an open source .NET tool designed to stress test databases with large data flows. The application performs two main test scenarios: [...]

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How to Test Cloud Database Software

Software Testing Magazine — Mon, 15 Aug 2022 15:51:29 +0000

Database testing is done to check the integrity of a database by finding and fixing its vulnerabilities. Without this process, the system might become unstable. Some or all of the stored information in the Cloud database may be rendered useless or worse, might become accessible by unauthorized personnel. Author: David Lees The testing of Cloud databases mainly involves testable components that are hidden from users, which is why it’s also called ‘backend testing’. These items include database management systems (DBMS), SQL servers, and other internal processes. When conducting database testing, you need to verify elements such as database tables, server validation, and stored procedures. Cloud database testing is much like traditional database testing. The main difference is that for the first one, you’ll be running the test on a cloud platform. Note that before you begin, be sure to conduct a review of the requirements and establish what role you have in the project. Our previous article ‘Best Practices Reviewing Requirements for Testability’ provided a sample scenario when testing a program on a new cloud platform. Another person or team may be tasked to handle the software setup, and you might be assigned to do the validation of the application. It’s vital to clarify these designations right from the start to avoid confusion and confirm accountability. Once that’s ironed out, it’s time to get on with the process, which involves the segments below: Create or Migrate Database and Automate Procedures Creating database instances can be done safely in a containerized Cloud environment with software [...]

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How to Write Good Test Cases for Database Testing: 4 Key Tips

Software Testing Magazine — Mon, 13 Jun 2022 12:44:28 +0000

When developing software, you will need to write test cases to help ensure that your code is working as expected. Writing good database testing scenarios can go a long way toward improving your application’s reliability and making it easier to maintain in the future. If you’re looking to get into database testing or just want to learn how to write better test scenarios, this article is for you. In this article, You’ll also learn four essential tips on how to write better test cases to ensure that your Database Tests are operating at peak performance. Identify The Scope And Purpose Of Testing Before you start writing any test cases, it’s a good idea to identify the scope and purpose of each one. Each test case’s purpose is to cover your code’s functionality and ensure that it works as expected. When thinking about the purpose of a test case, try to keep it as descriptive as possible. While developing your code, you’ll likely find that you need to write various test cases. Each with a different purpose. Depending on the functionality of your code, you may need to write different types of test cases. For example, suppose you have a model that contains information about customers and a web form that allows customers to place an order. In that case, you’ll need to write test cases to ensure that the information in your model is correct and the form is working as intended. Define How To Perform Testing Activities Once you’ve identified the [...]

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Best Practices for SQL Server Configuration Tuning and Improving Performance

Software Testing Magazine — Wed, 01 Dec 2021 22:12:36 +0000

If a SQL server is the bedrock of your app or service, then its performance will be a big part in determining the responsiveness and fluidity of the end-user experience. As such, it is only by monitoring database performance from moment to moment and tracking usage trends over time that you can optimize it successfully. Author: Richard Grant This is not always a straightforward process, but there are plenty of strategies and solutions to help you on your way. So here are just a few best practices to take onboard when it comes to SQL Server tuning and management. Image Source: Pixabay Make use of modern monitoring tools First of all, you cannot hope to handle the rigors of running a SQL database without the help of contemporary tools built to monitor and automate all sorts of aspects of this job. For example, this database monitoring tool is not only ideal for tracking all sorts of game-changing metrics, but also for improving their observability and thus making it a breeze to pinpoint issues and find suitable fixes. The best tools will work with on-premises as well as cloud-based servers. And with comprehensive, comprehensible visualization capabilities, you will be able to unpick problems and explain them to non-technical team members more easily. As you might expect, monitoring tools are just the starting point for effective database management. From here, you need to know what to do with the insights they offer and the alerts they churn out automatically, which brings us [...]

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Big Data: How to Test the Elephant?

Software Testing Magazine — Tue, 27 May 2014 14:53:18 +0000

Big Data is a big topic in software development today. When it comes to practice, software testers may not yet fully understand what is exactly Big Data. A tester knows that you need a plan for testing it. Since most Big Data lacks a traditional structure, how does Big Data quality look like? And what the are most appropriate software testing tools? This article tries to answer these questions. Author: Alexander Panchenko, A1QA, www.a1qa.com As more and more companies are adopting Big Data as a solution for data analysis the question arises: how can you determine a proper testing strategy for controlling this heavyweight “elephant”? The problem for software testing is magnified by a lack of clear understanding about what to test and how deep inside a tester should go. As a software tester, you need a clear definition of Big Data. Many of us improperly believe that Big Data is just a large amount of information. This is a completely incorrect approach. Actually, you don’t face Big Data when you work with an Oracle 2 petabytes database, but just a high load database. To be very precise, Big Data is a series of approaches, tools and methods for processing of high volumes of structured and (what is the most important) of unstructured data. The key difference of Big Data from “ordinary” high load-systems is the ability to create flexible queries. Big Data can be described by three “V”: Volume, Variety, and Velocity. In other words, you have to process [...]

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Testing Database Migration: Black Box or White Box?

Software Testing Magazine — Mon, 31 Mar 2014 14:13:10 +0000

Creating an effective data migration testing strategy is critical to reducing risk and delivering a successful migration. This article offers thoughts and recommendations on how to create a more consistent data migration testing methodology using either a black box or a white box approach. Author: Alexei Porodzinsky, A1QA, http://www.a1qa.com/ Data migration is a process that involves the migration of data from an existing database to a new one. Whenever an organization decides to upgrade or change its database, it will need to transport the existing data to the new database. The scope of data migration is much more than what the term suggests. Data migration activity typically will include everything that is required with respect to data to ensure that the new database is up and running without any defects and it also contains all the legacy data (data that is present in the outdated database), and the data has been migrated to correct tables and columns. So, the only way to insure its correctness is to test the migration process. The process of migration testing starts with the analysis of migration requirements, afterwards the approach is defined. The analysis bases upon such points as Type of data to be migrated Data sources Documentation analysis, describing the migration process Database alterations analysis Database structure and type Data storage format Analysis of migration method Migration approach As long as the tester is ready with the analysis, it is time to choose between the types of migration approach. There are three [...]

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SQL Server Unit Testing

Software Testing Magazine — Mon, 25 Feb 2013 17:31:46 +0000

The SQL Server unit tests feature have been added in the December 2012 update of SQL Server Data Tools (SSDT). This article presents a detailed information on how to create an run unit tests in SQL Server. The SQL Server unit tests are created in normal VB or C# Test projects and the MSTest infrastructure is used to run the tests and view the results. There are two ways to create SQL Server unit tests in a test project: you can generate tests from a database project opened in SQL Server Object Explorer (SSOX), which creates unit tests with a skeleton T-SQL script for you to complete, or you can manually add unit tests into a test project using the template introduced by SSDT. You can then run these unit tests from Visual Studio or MSTest. Read the complete article on http://msdn.microsoft.com/en-us/library/jj851200%28VS.103%29.aspx

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