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In the ever-evolving world of software development, architects and developers strive to create scalable, maintainable, and robust applications. One of the key principles that aid in achieving these goals is the proper organization of data access and storage. The Repository Pattern is a fundamental architectural design pattern that provides a structured approach to handling data, making it an invaluable tool for developers. In this article, we will delve into what the Repository Pattern is, how it should be implemented, and provide some real-world examples of its application.

MPU-9250 is one of the most advanced combined accelerometer, gyroscope and compass small size sensors currently available. It replaces the popular MPU-9150 lowering the power consumption, improving gyro noise and compass full scale range performance. It has many advanced features, including low pass filtering, motion detection and even a programmable specialized processor.

The Criteria Pattern stands as a powerful tool, often hidden in the shadows of more commonly discussed design patterns. This pattern empowers developers to implement dynamic and customizable queries in their applications, enhancing flexibility and maintainability To facilitate this process, Criteria package provides the shared domain logic that contains abstract criteria implementation that each specific criteria should extend from.

Pagination is a crucial aspect of modern web applications that deal with large datasets. When working with MongoDB, a popular NoSQL database, efficient pagination techniques become essential to retrieve and display data in a controlled manner. MongoDB provides various features and functions to achieve efficient pagination. In this article, we will examine these concepts, exploring how they can be used to implement pagination effectively in MongoDB.

MongoDB is a popular open source and document oriented database system. It belongs to a family of databases called NoSQL, which is different from the traditional table based SQL databases. It makes use of collections, each having multiple documents, and allows the user to store data in a non relational format. Data is stored in flexible, JSON-like documents where fields can vary from document to document. That's the reason for calling it schemaless database.