MongoDB is a tableless (NoSQL) and open-source database management system that stores, manages, and access document data based on JSON (JavaScript Object Notation). MongoDB was launched in 2009 by MongoDB Inc. is developed.
In MongoDB, data is stored as documents in the database. Each document contains one or more fields, and each field contains a value. Fields can contain different types, such as numbers, strings, dates, etc. Also, in MongoDB, a document can contain one or more subdocuments.
MongoDB uses the JavaScript programming language to execute queries and commands. Also, this database management system can support various programming languages such as Python, Java, Ruby, etc.
Due to its flexibility and high scalability, MongoDB is used in many applications, such as content management systems, online stores, data analysis applications, etc. Also, this database management system is used in many websites and applications due to its high speed, stability, and flexibility.
Generally, MongoDB is a tableless database management system used to store and manage JSON-based document data. The ability to support different programming languages, high speed, stability, and flexibility are among the most important features of MongoDB.
Advantages of MongoDB
As a tableless database management system (NoSQL), MongoDB has many advantages over relational database management systems (RDBMS). Below are some of these benefits:
1- Scalability
Scalability means the ability of the system to increase the capacity of data processing and storage by increasing its volume. To clarify, scalability refers to the ability of the system to add new resources to the system and distribute the parallel load among these resources.
MongoDB is easily scalable with a flexible structure and the ability to add new servers. This means new servers can be easily added to the system as the data volume increases. And as a result, it can increase scalability.
Adding new servers to the system makes it possible to increase the data storage and processing capacity easily. As a result, parallel loads can be established between the servers.
Also, MongoDB uses techniques such as load balancing (sharding) that allow developers to distribute data across multiple servers. Using load balancing, data can be stored in parallel on different servers. And as a result, it could increase scalability in MongoDB.
In general, increasing scalability in MongoDB improves system performance and increases the ability to manage large data. By using MongoDB, this advantage can be used to support applications that require large amounts of data and increase scalability.
2- NOSQL Support
MongoDB is a NoSQL database that uses the document model. In other words, in MongoDB, data is stored as documents. This data model allows developers to work with data and respond dynamically to new data easily.
One of the advantages of using a NoSQL database such as MongoDB is that these types of databases are suitable for applications that require large volumes of data and greater flexibility in data storage and retrieval. Also, due to their non-relational structure, NoSQL databases such as MongoDB support the ability to quickly and conveniently add new data.
In MongoDB, NoSQL support allows developers to work with data and dynamically respond to new data easily. MongoDB also allows developers to access data at the document level directly.
Overall, NoSQL support in MongoDB allows developers to easily work with large volumes of data and meet their application needs with the right data type.
3- Speed
MongoDB has advantages such as high speed in data storage and retrieval operations. This high speed is replaceable due to the internal structure and the use of information storage space (Storage Engine). This technology, due to storing data in BSON format to transfer JSON data and having features such as index, full-text search, and advanced analysis (Aggregation Framework), is The default is fast.
In MongoDB, a data storage space like WiredTiger is used, which has features like data compression, transaction management, support for binary indexes, etc. Also, MongoDB uses its query network called MQL (MongoDB Query Language). This feature allows developers to work with data and dynamically respond to new data easily.
Also, this technology uses techniques such as load balancing (sharding), which allows developers to distribute data between different servers. By using load balancing, data can be stored in parallel on different servers, and as a result, it can increase scalability and data processing speed in MongoDB.
In general, the high speed of storage operations and data mining allows developers to work with large and complex data and store and retrieve their data faster and more efficiently.
4- Support Charging Methods
MongoDB uses sharding to support the system’s parallel processing and load distribution. In this method, the data is divided into several parts or charges based on a key (for example, a specific field in the document), and different servers are used to process each part. This allows developers to increase scalability by adding new servers to the system and to work with large and complex data.
Using the charging method in this technology allows developers to store and process different parts of data in parallel and on different servers. This improvement in system performance increases scalability in MongoDB. Also, by using load balancing, data can be stored in parallel on different servers, and as a result, it can increase scalability in MongoDB.
In general, the support for charging methods in MongoDB allows developers to work with large and complex data and to increase scalability by adding new servers to the system.
5- Synchronization
MongoDB uses several methods to synchronize data. Among these methods, we can mention the Replication method, which allows developers to replicate data between several servers and perform data recovery automatically in case of failure of one of the servers.
In the replication method, data is replicated synchronously between different servers. This means that any changes made on one of the servers are also automatically applied to the other servers. Therefore, in case of failure of one of the servers, the data is automatically restored on the other servers, and users are transparently protected from the failure of the main server.
In MongoDB, other methods, such as load balancing, are also used, which increases scalability and synchronizes data between different servers. Using load balancing, data can be stored in parallel on different servers. And as a result, it could increase the scalability and synchronization of data in MongoDB.
In general, data synchronization in MongoDB using methods such as replicas and load balancing allows developers to work with large and complex data and automatically recover data in the event of a server failure.
6. Flexible Data Model
One of the key advantages of MongoDB is its flexible data model. In traditional relational databases, data is stored in tables with rows and columns, and the schema must be defined in advance. This approach works well for structured data, but it can be limiting for applications that deal with unstructured or semi-structured data.
In contrast, MongoDB uses a document-oriented data model, where data is stored as documents, which are similar to JSON (JavaScript Object Notation) objects. Each document consists of a set of key-value pairs, where the key identifies the data element and the value contains the data itself. Documents in MongoDB can be nested and can contain arrays and other complex data types, allowing for the storage of complex and unstructured data.
For example, consider a blog application that uses MongoDB to store blog posts. In a traditional relational database, the schema would need to be defined in advance, with columns for the post title, author, date, and content. However, with MongoDB, each blog post can be stored as a document with the following fields:
In this example, the document contains fields for the post title, author (nested document), date, and content. The schema is flexible and can be easily expanded to include additional fields without requiring changes to the database structure.
This flexible data model makes MongoDB well-suited for applications that deal with unstructured or semi-structured data, such as social media platforms, mobile applications, and e-commerce websites. It also makes it easier to develop and maintain applications, as changes to the data model can be made without requiring changes to the database schema.
7- Reliability
MongoDB has the advantage of high reliability for data storage and management. This capability is achieved through various methods, including replication, transactions, backup, and data recovery.
One of the methods that MongoDB uses to increase reliability is the replication method. In this method, data is replicated synchronously between different servers. Any changes made on one of the servers are also automatically applied to the other servers. Therefore, in case of failure of one of the servers, the data is automatically restored on the other servers, and users are transparently protected from the failure of the main server.
ACID transactions are also supported in MongoDB. This means that transactions in MongoDB are atomic. It means they are completely done and confirmed, or none of their changes have been applied. This feature allows developers to work with large and complex data and have high confidence in their data.
MongoDB also uses powerful backup and recovery methods that allow developers to back up and restore their data when needed easily.
8- Security
MongoDB has high-security advantages for data storage and management. This capability is achieved through various methods, including encryption, access management, advanced security posture, and support for secure networks.
One of the methods that this technology uses to increase security is data encryption. MongoDB uses AES key-based encryption. This allows developers to encrypt their sensitive data in the database.
MongoDB also uses comprehensive access management to protect data. Using data-based permissions, developers can restrict user access to various data and operations. MongoDB also uses input and output monitoring, intrusion detection, suspicious activity, and other critical events to ensure data security.
Also, this technology uses advanced security modes to support data security. These features include limiting data access, assigning roles, setting time limits for data access, detecting and tracking security threats, and security management of external access to data.
MongoDB also supports secure networks. These networks include SSL/TLS, SSH, and VPN, allowing developers to use secure networks to access their data.
Overall, MongoDB generally uses methods such as encryption, access management, advanced security posture, and support for secure networks., allowing developers to protect their sensitive data in the database easily.