Optimizing API Performance with Protocol Buffers FlatBuffers MessagePack and CBOR

Introduction

In today’s cloud-driven world, APIs are the backbone of modern applications. From microservices to IoT systems, APIs enable seamless data exchange between distributed components. However, as applications scale, the traditional JSON format often becomes a bottleneck, resulting in increased payload size, latency, and compute overhead.

To overcome these challenges, developers are adopting more efficient binary data formats that are faster to serialize, smaller in size, and better suited for high-performance environments. Among these, Protocol Buffers (Protobuf), FlatBuffers, MessagePack, and CBOR are the top contenders. Here’s how these formats work.

Why JSON Is Slowing Down Your Workloads?

JSON is great for readability, but not for efficiency.

Pros of JSON

• Human-friendly and easy to debug
• Natively supported by AWS SDKs, API Gateway, and Lambda
• Ideal for small payloads and public APIs

Cons of JSON

• High network cost: Text-based format means larger payloads → higher data transfer bills
• Slow AWS Lambda execution: Parsing JSON in Python, Node.js, or Java adds CPU time
• No strict typing: Inconsistent types can cause deserialization errors
• Storage overhead: Larger JSON logs and objects inflate Amazon S3 and Amazon CloudWatch storage

When you’re running millions of Lambda calls or IoT messages a day, this inefficiency directly translates into latency and cost, and that’s where binary formats come in.

Protocol Buffers (Protobuf)

Protocol Buffers (Protobuf), developed by Google, is a compact binary serialization format. It’s already used internally by AWS for services like App Mesh and Cloud Map, and it serves as the foundation of gRPC, which runs on AWS.

How It Works

You define your data schema in a .proto file, then generate code for your language using the protoc compiler. That generated code serializes and deserializes messages at lightning speed.

Why It’s Fast on AWS

• Binary format: Up to 80% smaller payloads → lower API Gateway costs
• Schema-based: Predictable structure for inter-service communication
• Precompiled access: Faster Lambda cold starts and execution
• gRPC integration: Works seamlessly with AWS App Mesh and EKS microservices

Common AWS Use Cases

• gRPC microservices running on ECS, EKS, or Lambda
• IoT Core devices sending telemetry in Protobuf to reduce payload size
• Kinesis / Firehose streams carrying structured binary data

Example

Instead of sending:

You send a binary Protobuf message, which is a fraction of the size and instantly decodable by any client with the corresponding .proto file.

Result: Smaller, faster payloads and reduced AWS data transfer costs.

FlatBuffers

FlatBuffers, also from Google, is built for real-time systems, such as gaming and IoT areas, where AWS plays a significant role through GameLift, IoT Greengrass, and Edge computing.

Unlike Protobuf, FlatBuffers don’t require deserialization. Data can be accessed directly from the buffer (zero-copy), making it incredibly fast.

Why It’s Fast on AWS

• Zero parsing overhead → Excellent for AWS Lambda or Amazon EC2 real-time processing
• Low memory usage → Ideal for IoT Edge devices
• High throughput → Faster streaming and telemetry handling

Common AWS Use Cases

• AWS IoT Greengrass: Send compressed, binary sensor data to the cloud
• AWS Lambda@Edge: Real-time request/response processing at CloudFront edge locations
• AWS GameLift: Real-time state synchronization in multiplayer games

Why It Helps

When your IoT device sends thousands of updates per second to AWS IoT Core, FlatBuffers can cut message size and CPU use by 60–80%.

MessagePack

MessagePack is often referred to as “binary JSON.” It maintains the same structure as JSON but compresses it into a binary format, eliminating the need for a schema.

This makes it the easiest AWS upgrade, allowing you to switch from JSON to MessagePack in your AWS Lambda, Amazon API Gateway, or AWS Step Functions with minimal code changes.

Why It’s Fast on AWS

• 50–70% smaller payloads compared to JSON
• Easy to integrate: Works with any AWS service expecting JSON (just serialize/deserialize before and after)
• Faster API Gateway responses and lower transfer cost

Common AWS Use Cases

• AWS Lambda + Amazon API Gateway: Compress REST/HTTP payloads
• Amazon Kinesis: Encode events efficiently in streams
• Amazon S3 + AWS Glue: Store and process compact binary logs

Example

Switching from JSON to MessagePack for a Lambda API that handles 1 million requests/day can reduce your Amazon API Gateway cost by 30–40% and AWS Lambda runtime by up to 25%.

CBOR

CBOR (Concise Binary Object Representation) is perhaps the most AWS-friendly format on this list, it’s natively supported in AWS IoT Core.

It’s similar to JSON but designed for constrained devices and low-bandwidth environments.

Why It’s Fast on AWS

• Built-in support in IoT Core SDKs and Rules Engine
• Binary encoding reduces network load
• Self-describing format (includes data types) for flexible processing

Common AWS Use Cases

• AWS IoT Core MQTT Messages: Devices can send CBOR payloads instead of JSON
• Lambda Processing: IoT Rules Engine triggers Lambda with CBOR payloads
• AWS IoT Analytics: Process compact telemetry data efficiently

Example

A temperature sensor sending CBOR messages via MQTT can reduce message size by 60%, allowing you to handle more devices within the same network bandwidth, resulting in a significant cost advantage in large IoT deployments.

Conclusion

They make your AWS architecture:

• Faster (lower latency, faster cold starts)
• Cheaper (smaller payloads, less transfer cost)
• More scalable (lightweight communication across services)

So, the next time you design an API, backend service, or IoT system, ask yourself:
“Do I need this data to be easily read by humans, or processed efficiently by machines?”
If it’s the latter, it may be time to move beyond JSON and adopt a binary format.

Drop a query if you have any questions regarding Binary data formats and we will get back to you quickly.

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