MongoDB is a popular NoSQL database that provides high performance, scalability, and flexibility for storing and retrieving data.

MongoDB offers flexible schema design, automatic sharding for horizontal scaling, built-in replication for high availability, and a rich query language for data retrieval.

In MongoDB, you can represent relationships between data using embedded documents or references. The choice depends on the nature of the data and the query patterns.

Indexes in MongoDB improve query performance by allowing the database to quickly locate the documents matching certain criteria. They are defined on specific fields or expressions.

CRUD operations (Create, Read, Update, Delete) in MongoDB are performed using the insert, find, update, and remove methods. These operations interact with the collections and documents.

Sharding in MongoDB is a technique for horizontal scaling where data is distributed across multiple machines in a cluster. It allows for increased data storage and higher throughput.

MongoDB Atlas is a fully managed cloud database service provided by MongoDB. It offers automated backups, scaling, and monitoring, making it easy to deploy and manage MongoDB in the cloud.

MongoDB ensures high availability through replica sets. A replica set is a group of MongoDB servers that maintain the same data set, providing redundancy and automatic failover.

The aggregation framework in MongoDB allows you to perform advanced data processing operations, such as grouping, filtering, and computing aggregations, using a pipeline of stages.

MongoDB Compass is a graphical user interface (GUI) tool provided by MongoDB for visually exploring and interacting with MongoDB data. It offers an intuitive way to query, analyze, and visualize data.

WiredTiger is the default storage engine in MongoDB since version 3.2. It provides support for document-level concurrency control, compression, and efficient data storage and retrieval.

SQL databases use a structured schema and are based on the relational model, while NoSQL databases like MongoDB use a flexible schema and can store data in various formats like documents, key-value pairs, or graphs.

MongoDB provides tunable data consistency. It offers strong consistency guarantees at the document level within a replica set, and eventually consistent reads across multiple replica sets in a sharded cluster.

MongoDB Compass Schema is a feature in MongoDB Compass that allows you to visualize and explore the structure of your MongoDB data. It provides a graphical representation of the database schema.

Indexes in MongoDB improve query performance by allowing the database to quickly locate the documents matching certain criteria. They are defined on specific fields or expressions.

The MongoDB aggregation pipeline is a framework for data aggregation and transformation. It allows you to process data records and apply multiple stages of operations, such as filtering, grouping, sorting, and projecting.

The oplog (operations log) in MongoDB is a capped collection that records all the write operations that modify data in a replica set. It allows secondary nodes to replicate and catch up with the primary node.

GridFS is a specification in MongoDB for storing and retrieving large files, such as images, videos, and audio files. It divides the file into smaller chunks and stores them as separate documents.

MongoDB transactions allow you to perform multiple operations on multiple documents in an atomic and isolated manner. It ensures that either all the operations succeed or none of them take effect.

The MongoDB Connector for BI is a tool that allows you to connect MongoDB with popular Business Intelligence (BI) and data visualization tools. It enables you to analyze and visualize MongoDB data using familiar BI tools.