Jupyter Notebook

Jupyter Notebook is primarily designed with Python in mind, and the extensive use of Python-specific features can make it challenging for users who are not familiar with this language.

Running complex or resource-intensive operations within a Jupyter Notebook can lead to slow execution times and potential crashes, especially when dealing with big datasets that exceed the memory capacity of the local machine.

Setting up Jupyter Notebooks with specific dependencies or integrating it into larger software development workflows can be complex and requires a good understanding of package management and environment configuration tools like Conda or Docker.

Jupyter Notebook's default settings may expose users to security risks, especially when running notebooks on public networks. It requires additional configurations for secure sharing and execution of code.