Liquibase & graphql

The Liquibase API consists of pluggable interfaces and the driving logic that surrounds them.

Even the main Liquibase code itself is layered between the API-level code which works purely with interfaces, and the implementation-level code which is written and auto-discovered exactly like external extensions are.

Through liquibase api we can create changelog.xml files which help us to apply sql query on each deployment environment. It is very systematic way of managing database.

To make it easy to spin up standardized test environments for testing, Liquibase has an abstraction around testcontainers.org at liquibase/extension/testing/testsystem.

The wrapper around Test Containers allows us to provide a simple configuration system, plus support testing databases that do not have Docker containers such as in-memory and cloud databases.

What is a GraphQL API?

A GraphQL API is a type of API that transforms how clients access data. Unlike REST APIs, which return fixed data at each endpoint, GraphQL allows clients to specify the required data and obtain it in a structured format. This provides unparalleled flexibility, enabling developers to make precise queries and avoid receiving redundant information.

Graphql api helps to generate schema on user interface & expose to the screen workable functionality. Helps in syncing with different projects & data on different levels.

Implementation of a GraphQL API

GraphQL Schema: It starts with the creation of a schema. It describes the data types and their interrelationships, establishing the groundwork for the API’s functionalities. It’s defined using the GraphQL Schema Language (GSL).

Definition of a data type in GraphQL:

type User { id: ID! name: String! email: String! age: Int articles: [Article]}

Resolvers: After defining the schema, resolvers are implemented. These functions retrieve the data for each field of a type. For example, a resolver would look in the database to get the articles associated with a user.

Queries and Mutations: Clients can perform queries to retrieve data from the API. Written in the GraphQL query language, they can include arguments to filter or paginate the results. Mutations allow creating, updating, or deleting data on the server.

Example of a GraphQL query:

query { user(id: "123") { name email articles { title content } }}

Validation and execution of queries: Before being executed, the API validates the query against the schema to ensure its structure and security. Then, the API executes the query using the proper resolvers to obtain the required data.

Returning data to the client: The data is returned to the client in the requested format, usually JSON, although other formats can be supported.

Practical cases

GitHub implements GraphQL in its API, providing flexible access to features such as repository management and pull requests.

Meta, along with Instagram, uses GraphQL to efficiently deliver data to its millions of users.

Twitter employs GraphQL in its API, enhancing the retrieval of tweets, user profiles, hashtags, and trends.

Conclusion

In summary, GraphQL represents a significant advancement in APIs, with its flexible and efficient data management. Offering precise data retrieval, auto-generated documentation, continuous evolution without disruptions, and fewer excessive queries, it becomes a preferred choice for developers. With its adoption by well-known companies, it’s clear that its role will be crucial in the future of software.

Using GraphQL, developers can build more robust and high-performance applications, meeting current requirements for digital data management.