Feature stores are specialized data management systems designed to store, manage, and serve features used in machine learning models. Features are the independent properties or variables that serve as inputs for these models, playing a crucial role in their performance. By centralizing feature storage, feature stores facilitate the reuse of features across different models, ensuring consistency and efficiency in the machine learning workflow. They also support real-time data access and versioning, which are essential for deploying models in production environments. Overall, feature stores enhance collaboration among data scientists and streamline the model development process.