MongoDB is a powerful open-source document database that falls under the NoSQL category, distinguishing it from traditional SQL databases like MySQL and PostgreSQL. In MongoDB, data is stored in flexible JSON-like documents, allowing for dynamic and schema-less data storage.
Introduction to MongoDB
MongoDB is a free and open-source document database that is part of the NoSQL family of databases. Unlike traditional SQL databases, such as MySQL and PostgreSQL, MongoDB stores data in flexible JSON-like documents. This allows fields to vary from document to document and eliminates the need for a predefined schema. MongoDB’s data structure can evolve over time.
Features and Advantages of MongoDB
MongoDB is a popular NoSQL (Not Only SQL) database that offers various features and advantages for developers and businesses. Here are some key features and advantages of MongoDB:
1. Flexible Schema:
- MongoDB uses a flexible document-based data model, which means each document in a collection can have its own unique structure. This schema-less approach allows developers to store data without a predefined schema, making it easier to adapt to changing data requirements.
2. JSON-Like Documents:
- Data in MongoDB is stored in BSON (Binary JSON) format, which is a binary representation of JSON (JavaScript Object Notation). This format makes it easy to work with data in a format similar to native data types in programming languages.
3. Scalability:
- MongoDB is designed to scale horizontally, making it suitable for handling large amounts of data and high traffic loads. You can distribute data across multiple servers, or nodes, using features like sharding, which improves both read and write scalability.
4. High Performance:
- MongoDB is known for its high-performance capabilities, especially when used for read-heavy operations. It uses memory-mapped files for storage and supports indexes for efficient data retrieval.
5. Replication:
- MongoDB provides built-in support for replica sets, which are multiple copies of the same data. Replica sets offer high availability and data redundancy. If one node goes down, another can take over, ensuring continuous service availability.
6. Automatic Failover:
- In a MongoDB replica set, if the primary node fails, the system automatically elects a new primary node, minimizing downtime and ensuring data consistency.
7. Horizontal Scaling:
- MongoDB’s sharding feature allows you to distribute data across multiple servers or clusters, enabling horizontal scaling. This helps maintain performance as your data and user base grow.
8. Rich Query Language:
- MongoDB supports a powerful query language that includes features like filtering, sorting, aggregation, text search, and geospatial queries. This makes it suitable for a wide range of use cases, from content management to analytics.
9. Geospatial Indexing:
- MongoDB provides geospatial indexing, making it suitable for location-based applications. You can perform complex geospatial queries to find nearby locations or analyze spatial data.
10. Flexible Data Modeling: – With MongoDB’s flexible schema, you can model your data in a way that matches your application’s needs. This allows for the easy addition or removal of fields as requirements change.
11. Community and Ecosystem: – MongoDB has a large and active open-source community, which contributes to its ecosystem. You can find numerous drivers, libraries, and tools that support MongoDB integration with various programming languages and platforms.
12. Document-Level Locking: – MongoDB uses document-level locking for write operations, which means different documents in the same collection can be updated concurrently. This improves write performance and reduces contention.
13. Aggregation Framework: – MongoDB offers a powerful aggregation framework that allows you to perform complex data transformations, calculations, and aggregations directly within the database.
14. Built-in Replication Monitoring: – MongoDB provides tools for monitoring the health and status of replica sets, making it easier to manage and maintain a robust database infrastructure.
15. Commercial Support: – MongoDB, Inc. offers commercial versions of MongoDB, including MongoDB Atlas, a Database as a Service (DBaaS) platform. This provides enterprises with professional support, security features, and management tools.
Installing MongoDB on Ubuntu 20.04
Step 1: Import MongoDB Public Key
Before installing MongoDB, you need to import the public GPG key to ensure the authenticity of the software.
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wget -qO - https://www.mongodb.org/static/pgp/server-5.0.asc | sudo apt-key add -
Verify that the key was successfully added:
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sudo apt-key list | grep "MongoDB"
Step 2: Add MongoDB Repository to Source List
Add the official MongoDB repository to your system’s source list to fetch the latest MongoDB package.
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echo "deb [ arch=amd64,arm64 ] https://repo.mongodb.org/apt/ubuntu $(lsb_release -cs)/mongodb-org/5.0 multiverse" | sudo tee /etc/apt/sources.list.d/mongodb-org-5.0.list
Update the package list:
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sudo apt update
Step 3: Install MongoDB on Ubuntu 20.04
With the MongoDB repository added, you can now install the latest stable version using the following command:
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sudo apt install mongodb-org
Step 4: Running MongoDB
To run MongoDB, start the mongod service (MongoDB daemon):
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sudo systemctl start mongod
If you encounter an error like “service not found,” use this command:
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sudo service mongod start
Verify the status of the mongod service:
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sudo systemctl status mongod
To start MongoDB automatically at each boot, enable the service:
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sudo systemctl enable mongod
Step 5: Accessing MongoDB Shell
To access the MongoDB shell from the same system running the mongod process, use the following command:
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mongo
Conclusion
This guide has provided you with the steps to install MongoDB Community Edition on Ubuntu 20.04. MongoDB’s flexibility, scalability, and powerful features make it a popular choice for developers working with dynamic and evolving data structures. With MongoDB installed and running, you can explore its capabilities and build applications that take advantage of its NoSQL document-based approach.
