Data representations like JSON and XML act as the “language” APIs use to structure and format the information being exchanged. A data representation provides a standardized way to structure data, making it understandable for both the sender (API server) and the receiver (client application).
Common representations include:
- JSON
- XML
- Protobufs
- YAML
JSON (JavaScript Object Notation)
JSON is the most common data representation used today since it integrates seamlessly with JavaScript, is human-readable (and thus is easier to debug), and is simple to use.
It’s structured with key-value pairs, nested objects, and arrays for flexible modeling of data relationships.
Example:
{
"product_id": 12345,
"name": "Widget X",
"price": 9.99
}
XML (Extensible Markup Language)
XML is used less in today’s world, but offers a highly customizable way of structuring data using tags and attributes. It’s popular for legacy systems or scenarios requiring granular data definitions.
It’s structured as a hierarchical model with nested elements.
Example:
<product>
<product_id>12345</product_id>
<name>Widget X</name>
<price>9.99</price>
</product>
Protocol Buffers (Protobufs)
Protobufs are a binary format designed by Google that is known for its efficiency and speed. It’s used in microservices and large scale systems, where the “weight” of JSON starts increasing bandwidth compared to using Protobufs, which can be over half the size of the equivalent JSON representation.
It comes with robust APIs and is great for environments where multiple programming languages are used.
Example:
syntax = "proto3";
message ChatMessage {
string sender_id = 1;
string content = 2;
int64 timestamp = 3;
}
YAML (Yet Another Markup Language)
YAML prioritizes human readability above all, so it’s mostly used for config files. In APIs, it’s not used often.
Example:
product:
id: 12345
name: Widget X
description: "The ultimate widget for all your widgeting needs."
price: 9.99
categories:
- gadgets
- tools
Comparing Data Representations
Representation | Description | Strengths | Ideal Use Cases |
JSON | Employs key-value pairs and arrays. | Simple, lightweight, web-friendly, broadly supported. | General-purpose APIs, web services, frontend interactions. |
XML | Hierarchical structure with tags and attributes. | Highly customizable, supports strict schemas, legacy compatibility. | Complex data with custom tagging, data exchange with legacy systems, industry-specific standards. |
Protocol Buffers | Binary format with a defined schema. | Extremely efficient (size and speed), cross-platform and cross-language. | High-performance APIs, microservices, real-time data exchange, large volume data transfer. |
YAML | Prioritizes readability and ease of editing. | Human-friendly, well-suited for configuration data. | APIs requiring clarity and manual data editing, configuration files. |