Feature stores are specialized data management systems designed to store, manage, and serve features used in machine learning models. Features are the independent variables or properties that serve as inputs for these models, playing a crucial role in their performance. By centralizing feature storage, feature stores facilitate easier access, sharing, and reuse of features across different projects and teams. This not only enhances collaboration but also ensures consistency and efficiency in the machine learning workflow. As organizations increasingly adopt machine learning, feature stores have emerged as essential components in the data pipeline, bridging the gap between data engineering and model deployment.