Apache Avro website screenshot

Apache Avro

Apache Avro is a data serialization system that provides rich data structures, a compact binary format, and container files for storing persistent data. Avro uses JSON for defining data types and protocols, and serializes data in a compact binary format.

Apache Avro publishes 1 API on the APIs.io network. Tagged areas include Apache, Big Data, Binary Format, Data Serialization, and Schema Evolution.

The Apache Avro catalog on APIs.io includes 2 Spectral governance rulesets.

Apache Avro’s developer surface includes documentation and 6 more developer resources.

17.4/100 emerging ▬ flat Agent 3/100 human only Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0
AccessFreemium
1 APIs 8 Features 5 Use Cases
ApacheBig DataBinary FormatData SerializationSchema Evolution

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0
Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from github.com/api-evangelist/avro: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

APIs 1

Individual APIs this provider publishes, each with its own machine-readable definition.

Apache Avro Schema Format

JSON Schema for validating Apache Avro schema definitions. Covers all Avro types including primitive types (null, boolean, int, long, float, double, bytes, string), complex type...

Pricing Plans 1

Published pricing tiers and plan structures.

Avro Plans Pricing

3 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Avro Rate Limits

5 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals for API financial operations.

Avro Finops

FINOPS

Features 8

Notable capabilities this provider offers.

Schema-First Design

Avro requires schemas to be defined in JSON before serialization, enabling strong typing and schema validation.

Schema Evolution

Avro supports backward, forward, and full schema compatibility through aliases, defaults, and type promotions.

Compact Binary Format

Avro serializes data in a compact binary format without field names, reducing payload size significantly.

Rich Type System

Supports primitive types, complex types (records, enums, arrays, maps, unions, fixed), and logical types (date, time, decimal, UUID).

Language Agnostic

Official implementations in Java, Python, C, C++, C#, PHP, Ruby, and Rust with broad ecosystem support.

Container Files

Avro Object Container Files (OCF) embed the schema with the data for self-describing data files.

RPC Support

Avro defines an RPC protocol mechanism using schemas for both request and response messages.

Kafka Native Format

Apache Kafka ecosystem uses Avro as a primary serialization format with the Confluent Schema Registry.

Scroll for all 8

Spectral Rules 2

Spectral governance rulesets for linting and validating these APIs.

Apache Avro API Rules

6 rules · 5 warnings 1 info

SPECTRAL

Apache Avro API Rules

15 rules · 9 errors 4 warnings 2 info

SPECTRAL

Security Posture 2

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Avro Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Avro Vulnerability Disclosure

security.txt · contact published

SECURITY

Use Cases 5

What developers build with this provider.

Event Streaming

Serialize Kafka events with Avro schemas stored in a Schema Registry for high-throughput data pipelines.

Data Lake Storage

Store large datasets in Avro container files in Hadoop-compatible storage with embedded schema metadata.

Schema Registry Integration

Use Confluent Schema Registry to manage schema versions and enforce compatibility across producers and consumers.

Inter-Service Messaging

Define message contracts between microservices using Avro schemas for type-safe data exchange.

Batch Data Processing

Process large volumes of structured data with Apache Spark, Hive, or Flink using Avro as the interchange format.

Integrations 6

Pre-built integrations with other platforms and tools.

Apache Kafka

Native serialization format for Kafka messages via the Confluent Schema Registry and Kafka clients.

Apache Spark

Spark SQL and DataFrames support reading and writing Avro files natively.

Apache Hive

Hive tables can be backed by Avro container files with schema stored in the Hive Metastore.

Confluent Schema Registry

Centralized schema management service for validating and evolving Avro schemas in Kafka ecosystems.

Apache Flink

Flink supports Avro for serialization and deserialization of streaming data.

Apache Hadoop

Avro is a native storage format supported by the Hadoop ecosystem for distributed processing.

Resources

Documentation 1

Reference material describing how the API behaves

Design & Contract 2

Pagination, idempotency, versioning, errors, and events

Build 1

SDKs, sample code, and the tooling you integrate with

Access & Security 2

Authentication, authorization, and security posture

Company 1

The organization behind the API

Source (apis.yml)

apis.yml Raw ↑
aid: avro
name: Apache Avro
description: Apache Avro is a data serialization system that provides rich data structures, a compact binary format, and container
  files for storing persistent data. Avro uses JSON for defining data types and protocols, and serializes data in a compact
  binary format.
type: Index
deliveryModel:
  model: unknown
  open_source: false
  commercial: false
  callable_host: false
  label: Delivery model not determined — needs a product licence on record
  confidence: low
  source:
  - none
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: freemium
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Freemium
  confidence: medium
  source:
  - plans
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/avro.png
tags:
- Apache
- Big Data
- Binary Format
- Data Serialization
- Schema Evolution
url: https://raw.githubusercontent.com/api-evangelist/avro/refs/heads/main/apis.yml
created: '2025-01-01'
modified: '2026-04-19'
specificationVersion: '0.23'
apis:
- aid: avro:avro-schema
  name: Apache Avro Schema Format
  description: JSON Schema for validating Apache Avro schema definitions. Covers all Avro types including primitive types
    (null, boolean, int, long, float, double, bytes, string), complex types (records, enums, arrays, maps, unions, fixed),
    logical types, and schema evolution features like aliases and default values.
  humanURL: https://avro.apache.org/docs/current/specification/
  tags:
  - Data Serialization
  - JSON
  - Schema
  - Schema Evolution
  properties:
  - type: Documentation
    url: https://avro.apache.org/docs/current/specification/
  - type: JSONSchema
    url: json-schema/avro-schema.yml
common:
- type: VulnerabilityDisclosure
  url: security/avro-vulnerability-disclosure.yml
- type: DomainSecurity
  url: security/avro-domain-security.yml
- type: Website
  url: https://avro.apache.org/
- type: Documentation
  url: https://avro.apache.org/docs/
- type: GitHubOrganization
  url: https://github.com/apache/avro
- type: SpectralRules
  url: https://raw.githubusercontent.com/api-evangelist/avro/refs/heads/main/rules/avro-spectral-rules.yml
- type: Vocabulary
  url: https://raw.githubusercontent.com/api-evangelist/avro/refs/heads/main/vocabulary/avro-vocabulary.yaml
- type: Features
  data:
  - name: Schema-First Design
    description: Avro requires schemas to be defined in JSON before serialization, enabling strong typing and schema validation.
  - name: Schema Evolution
    description: Avro supports backward, forward, and full schema compatibility through aliases, defaults, and type promotions.
  - name: Compact Binary Format
    description: Avro serializes data in a compact binary format without field names, reducing payload size significantly.
  - name: Rich Type System
    description: Supports primitive types, complex types (records, enums, arrays, maps, unions, fixed), and logical types
      (date, time, decimal, UUID).
  - name: Language Agnostic
    description: Official implementations in Java, Python, C, C++, C#, PHP, Ruby, and Rust with broad ecosystem support.
  - name: Container Files
    description: Avro Object Container Files (OCF) embed the schema with the data for self-describing data files.
  - name: RPC Support
    description: Avro defines an RPC protocol mechanism using schemas for both request and response messages.
  - name: Kafka Native Format
    description: Apache Kafka ecosystem uses Avro as a primary serialization format with the Confluent Schema Registry.
- type: UseCases
  data:
  - name: Event Streaming
    description: Serialize Kafka events with Avro schemas stored in a Schema Registry for high-throughput data pipelines.
  - name: Data Lake Storage
    description: Store large datasets in Avro container files in Hadoop-compatible storage with embedded schema metadata.
  - name: Schema Registry Integration
    description: Use Confluent Schema Registry to manage schema versions and enforce compatibility across producers and consumers.
  - name: Inter-Service Messaging
    description: Define message contracts between microservices using Avro schemas for type-safe data exchange.
  - name: Batch Data Processing
    description: Process large volumes of structured data with Apache Spark, Hive, or Flink using Avro as the interchange
      format.
- type: Integrations
  data:
  - name: Apache Kafka
    description: Native serialization format for Kafka messages via the Confluent Schema Registry and Kafka clients.
  - name: Apache Spark
    description: Spark SQL and DataFrames support reading and writing Avro files natively.
  - name: Apache Hive
    description: Hive tables can be backed by Avro container files with schema stored in the Hive Metastore.
  - name: Confluent Schema Registry
    description: Centralized schema management service for validating and evolving Avro schemas in Kafka ecosystems.
  - name: Apache Flink
    description: Flink supports Avro for serialization and deserialization of streaming data.
  - name: Apache Hadoop
    description: Avro is a native storage format supported by the Hadoop ecosystem for distributed processing.
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

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