MongoDB Flashcards

**MongoDB** is a non-relational NoSQL database that stores data in the form of documents. These documents are stored in BSON format, which is a binary representation of the JSON format.

MongoDB provides certain key features that distinguish it from traditional relational databases. Firstly, it is document-oriented, which means that each document can have its unique structure. Documents are grouped into collections, which are equivalent to tables in relational databases.

Secondly, MongoDB offers horizontal scalability, meaning that more machines can be added to a cluster to increase the database's capacity.

Thirdly, MongoDB supports ad-hoc queries, indexing, and data aggregation, allowing for the creation of complex queries and data analysis.

MongoDB is an ideal database for applications that require a high degree of flexibility and scalability, such as web, mobile, or IoT applications.

A collection in MongoDB is the equivalent of a table in a relational database. It is the place where MongoDB documents are stored.

Documents in collections are sets of key-value pairs. Documents have a dynamic schema. This means that documents in the same collection do not need to have the same set of fields, and the structure of those fields can vary from one document to another.

All of this means that MongoDB is very flexible and can adapt to various application requirements. Collections do not require a predefined structure. Instead, documents can contain fields with a dynamically defined structure, allowing different types of data with varying structures to be stored within the same collection.

There are no rigid rules regarding structure and data types. MongoDB allows storing documents with a complex shape - for example, documents containing other documents or arrays of other documents.

Sharding in MongoDB is a strategy for dividing large datasets into smaller, more manageable pieces (called shards), which are stored across multiple servers. This technique, also known as horizontal data partitioning, allows for efficient management and processing of high-volume data.

Despite being divided, the data in MongoDB is presented as a single, cohesive database. This means users do not have to change the way they reference the data, even if it has been partitioned.

The main goal of sharding is to improve performance and scalability. Dividing data into shards allows for a balanced distribution of the load across multiple machines, which directs resources to specific tasks and increases processing efficiency. This is crucial for large databases, where processing large amounts of data on a single server would be time-consuming and inefficient. Depending on the needs, shards can be distributed across different servers, clusters, or data centers, providing flexibility and reliability.

Replication in MongoDB allows for maintaining multiple copies of the same data across multiple machines. This facilitates high data availability and is a key aspect of MongoDB’s architecture.

MongoDB replication involves replica sets, which consist of **one primary node** (capable of handling write operations) and **two or more secondary nodes**. There can only be one primary member in a replica set at a time. In the event of its failure, the remaining secondary nodes can vote on which one should replace it.

Secondary nodes replicate data from the primary node, thereby maintaining copies of the dataset. When working with replication, it is important to ensure proper delayed replication and replication across separate data centers to ensure data protection.

Having these data copies allows MongoDB users to easily rebuild and restore data, facilitating quick recovery in case of a failure. In addition to enhancing availability, replication leads to increased read performance, as read operations can be performed on any member in the replica set.