Protobuf vs Apache Avro: The Complete Comparison

Both Protocol Buffers and Apache Avro are battle-tested binary serialization formats used by major tech companies. Both are fast, compact, and support schema evolution. So which one should you choose?

The answer depends on your use case. Protobuf excels at RPC and microservices. Avro dominates big data and streaming. This guide breaks down the real differences with benchmarks and practical advice.

If you're already familiar with Protobuf and comparing with JSON, check out ourProtobuf vs JSON comparison.

Quick Overview

Feature-by-Feature Comparison

Schema Definition Styles

Both use schemas, but the approach is very different. Let's compare the same data structure:

syntax = "proto3";

message Subscriber {
  string msisdn = 1;
  string name = 2;
  int32 account_balance = 3;
  bool is_active = 4;
  
  enum PlanType {
    PREPAID = 0;
    POSTPAID = 1;
  }
  PlanType plan = 5;
  
  repeated string services = 6;
}

{
  "type": "record",
  "name": "Subscriber",
  "fields": [
    {"name": "msisdn", "type": "string"},
    {"name": "name", "type": "string"},
    {"name": "account_balance", "type": "int"},
    {"name": "is_active", "type": "boolean"},
    {
      "name": "plan",
      "type": {
        "type": "enum",
        "name": "PlanType",
        "symbols": ["PREPAID", "POSTPAID"]
      }
    },
    {"name": "services", "type": {"type": "array", "items": "string"}}
  ]
}

The 3 Critical Differences

// Adding a field: just pick next number
string email = 7;  // Safe!

// Can rename with aliases
{"name": "email", "type": "string", "aliases": ["email_address"]}

Performance Benchmarks

Real-world benchmarks on a telecom subscriber record (8 fields, ~200 bytes original):

When to Choose Each

Quick Code Comparison

import subscriber_pb2

# Create message
subscriber = subscriber_pb2.Subscriber()
subscriber.msisdn = "+91-9876543210"
subscriber.name = "Telecom User"
subscriber.plan = subscriber_pb2.Subscriber.POSTPAID
subscriber.services.extend(["Voice", "Data"])

# Serialize
data = subscriber.SerializeToString()
print(f"Size: {len(data)} bytes")  # ~82 bytes

import avro.io
import avro.schema

# Load schema
schema = avro.schema.parse(open("subscriber.avsc").read())

# Create message
subscriber = {
    "msisdn": "+91-9876543210",
    "name": "Telecom User",
    "plan": "POSTPAID",
    "services": ["Voice", "Data"]
}

# Serialize
writer = avro.io.DatumWriter(schema)
bytes_io = io.BytesIO()
encoder = avro.io.BinaryEncoder(bytes_io)
writer.write(subscriber, encoder)
data = bytes_io.getvalue()
print(f"Size: {len(data)} bytes")  # ~95 bytes (no schema)

Ecosystem & Tooling

Can You Use Both?

Yes! Many companies do. Here's a common pattern:

Example: Netflix uses Protobuf for their API Gateway and Avro for Kafka event streams. This gives best-of-both-worlds.

Related Resources

External References

The Verdict

Both are light-years ahead of JSON or XML in terms of performance. The "wrong" choice between Protobuf and Avro is still way better than sticking with text formats at scale.