Challenges of Under-Fetching
1. Data Inconsistencies
- Inadequate data retrieval can lead to inconsistencies and inaccuracies in the program state.
- This can cause the application to behave incorrectly or produce inaccurate results.
2. Increased Latency
- Apart from this, sometimes, a few additional round trips or queries may have to be executed to fill the gaps, thereby slowing down the end-to-end response time and resulting in a degraded overall performance, particularly in data sources that are distributed or remote.
3. User Frustration
- Data retrieval that is not up to the mark might lead to user frustration and dissatisfaction.
What Are Over-Fetching and Under-Fetching?
Fetching data in GraphQL is a fundamental concept that involves retrieving information from a server or database. Unlike traditional REST APIs, GraphQL allows clients to request only the specific data they need, minimizing over–fetching and under–fetching.
In this article, We will explore the concepts of fetching, over–fetching, and under–fetching in GraphQL, along with their challenges and solutions in detail and so on.
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