This quickstart describes how to connect an application to a database in Azure SQL Database and perform queries using Python and the mssql-python driver. The mssql-python driver has built-in support ...

As a data scientist, you need Python for detailed data analysis, data visualization, and modeling. However, when your data is stored in a relational database, you need to use SQL (Structured Query ...

Application requests to Azure SQL Database must be authenticated. Although there are multiple options for authenticating to Azure SQL Database, you should prioritize passwordless connections in your ...

Rodrigo Ribeiro Gomes, Head of Innovation at Power Tuning, has been leveraging the new AI features in SQL Server engine to simplify the lives of DBAs and developers. He generously shared his ...

If you’ve worked with databases in Python, you know the boilerplate: open a connection, create a cursor, run queries, commit or rollback transactions, close cursors and connection. Forgetting just one ...

Need help choosing the best Python ORM for your projects? Here's what you need to know about SQLAlchemy, PonyORM, Django ORM, Peewee, SQLObject, and Tortoise ORM. When you want to work with a ...

Data transformations are the engine room of modern data operations — powering innovations in AI, analytics and applications. As the core building blocks of any effective data strategy, these ...

SQL is extremely good for data retrieval and calculating basic statistics, whereas Python comes into its own when you need in-depth, flexible exploratory data analysis or data science. What if you ...

Data scientists play a crucial role in extracting valuable insights from large datasets. To achieve this, they rely on robust programming languages and tools. SQL and Python are among the most popular ...

The Cloud SQL Python Connector is a Cloud SQL connector designed for use with the Python language. Using a Cloud SQL connector provides a native alternative to the Cloud SQL Auth Proxy while providing ...