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Docker technology is gradually winning its place in enterprise applications. As an efficient virtualization technology, Docker allows development/operation and maintenance personnel to independently deploy applications in containers and run them in different environments in a relatively consistent manner. In addition, Docker also brings other benefits to enterprises, one of the important benefits is the ability to accelerate application development and deployment.
For most enterprises, the database is the core of the application. Therefore, if the database can be integrated into a Docker container, enterprises can better manage different versions of database instances and deploy the database more quickly.
What is the relationship between Docker technology and database?
Docker containers are mainly used to deploy applications. Running applications in containers has many benefits, such as better portability, scalability, and security. However, running a database in a container can present some challenges.
First of all, databases usually require large amounts of memory and CPU resources to handle large numbers of data requests during periods of high load. In a containerized environment, this resource demand can lead to container crashes or resource contention between containers.
Secondly, the database usually needs to provide some data durability guarantees to ensure that the data will not be lost when the container restarts or crashes. However, in containers, it is difficult to achieve data persistence guarantees. This has inspired enterprises to look for solutions that guarantee data integrity and durability in the event of a completely new container.
To solve these challenges, enterprises can use some special tools and techniques to integrate the database into Docker containers to run the database on the container. Let’s introduce some open source database containerization solutions.
Containerized database solution
MySQL is a widely used relational database system, and there are many solutions for Docker containers Open source solutions. These solutions can be roughly divided into two categories:
a) Build a container using the official MySQL image: In this solution, the MySQL version running in the Docker container is the same as the MySQL version on the host. However, in the official MySQL image, MySQL data is unstable, and container exit may cause data loss. If you want to solve this problem, you may need to use an external volume or data volume container.
b) Use a temporary MySQL container: Using this method, you can create a custom MySQL container through tools such as Docker Compose, which will serve as the host for the database container. This container can install some additional packages to meet the specific needs of the enterprise. You can then map this container to the host for data persistence and stability.
PostgreSQL is an open source object-relational database system with many advanced features, and there are solutions to containerize it.
a) Use a container built from the official PostgreSQL image: This solution is similar to MySQL. You can build a container using the official PostgreSQL image and then run a PostgreSQL instance in the container. However, data may be lost by default, so some specific configuration is required to save the data.
b) Use a custom PostgreSQL container: Also similar to the MySQL solution, you can create a custom PostgreSQL container in a tool like Docker Compose and install the required packages in it. You can then map this container to the host for data persistence and stability.
MongoDB is a popular NoSQL database. Unlike relational databases, NoSQL databases generally do not use tables and row structures, but instead use key-value pairs and document data types. This makes MongoDB containerization relatively simple, as they do not need to follow the first and second regularization rules. There are some containerization solutions that can help you launch MongoDB instances on Docker.
a) Use a container built from the official MongoDB image: You can build a container using the official MongoDB image and run a MongoDB instance in it. This way no additional work is required.
b) Use a custom MongoDB container: This approach is similar to MySQL and PostgreSQL containerized solutions. You can create a custom MongoDB container in a tool like Docker Compose and install the required packages. You can then map this container to the host for data persistence and stability.
Summary
The emergence of Docker technology makes it easier for enterprises to manage and deploy applications, but running databases in containers will face some challenges. To this end, the open source community provides many containerization solutions to help enterprises deploy and manage databases in Docker containers. Whether in MySQL, PostgreSQL or MongoDB, there are solutions for Docker containers. Enterprises can choose their favorite database, apply the above method to treat it as a module in a Docker container, and make full use of the advantages of Docker technology to deploy and manage databases faster.
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