Data Serialization in Distributed Systems
Explore key data serialization formats, such as XML, JSON, Protobuf, Avro, and Thrift, and learn how to select the right one for a specific use case.
In a distributed system, services must constantly exchange information to function.
This communication breaks down if a service written in Python cannot understand data sent from a service written in Java. This is where data serialization comes in. It translates data structures into a format that can be stored or transmitted and then reconstructed later.
Serialization is a fundamental building block for achieving scalability and interoperability in modern architecture.
In real-world System Design, choosing the right format directly impacts performance, data size, and how easily our system can evolve. In interviews, showing awareness of these trade-offs is just as important. To understand these trade-offs, we’ll divide the most common formats into two broad categories.
We’ll start with textual formats like XML and JSON, prized for their human-readability. Then, we’ll dive into high-performance binary formats, such as Protocol Buffers, Thrift, and Avro, which are optimized for speed and efficiency. This will equip us to select the right tool for any communication challenge.
Textual data formats
Textual formats represent data using human-readable characters, making them easy to read and debug. They are often schemaless, meaning the data’s structure is embedded within the message itself, which provides flexibility. We’ll explore the two most common textual formats: XML and JSON.
Extensible Markup Language (XML)
XML was a foundational format for early web services. It uses a tag-based syntax similar to HTML but allows for custom tags to define data structures. A key feature of XML is the use of attributes within tags to provide metadata, which can be useful for filtering or describing the data.
However, XML is extremely verbose. As the example below highlights, the use of opening and closing tags for every element, along with attributes, results in larger payload sizes and slower parsing compared to more modern formats.
Due to these performance drawbacks, XML is rarely used for new, high-performance APIs and has largely been replaced by more lightweight formats, such as JSON. ...