JSON Schema to Apache Avro Converter

Convert JSON Schema definitions into strongly typed Apache Avro (.avsc) record schemas in your browser.

At a glance

JSON Schema to Apache Avro Converter translates JSON Schema models into Apache Avro Schema (.avsc) record definitions. It accurately translates primitive types, logical formats like timestamp-millis and uuid, optional union fields, nested records, and maps into valid Avro specifications in browser memory.

100% Client-Side In-Browser JSON Schema to Apache Avro Converter

Convert JSON Schema (Draft-04 to 2020-12) models directly into strongly typed Apache Avro (.avsc) record definitions in browser memory.

Pure In-Browser
Sample Presets:
Valid Schema 0 chars

Generation Options

Lines
0
Record Fields
0
Record Name
-
Namespace
com.example
Type Mapping Highlights: date-time → timestamp-millis, uuid → uuid logical type, additionalProperties → map, and optional non-required properties → ["null", type].

Why Use This JSON Schema to Apache Avro Converter?

100% Client-Side Privacy: Your schema contracts and proprietary data models never leave your local device.
Multi-Draft Support: Seamlessly handles Draft-04, Draft-06, Draft-07, Draft 2019-09, and Draft 2020-12.
Logical Types Resolution: Automatically maps date-time to timestamp-millis, date to date, and uuid to uuid.
Nullable Union Handling: Safely translates optional properties into Avro [null, type] unions with null defaults.

How to Use JSON Schema to Apache Avro Converter

1

Paste JSON Schema Definition

Enter your JSON Schema JSON or drop a .json schema file into the editor.

2

Configure Avro Settings

Customize Avro namespace, fallback root record name, and toggle logical type mappings.

3

Copy or Download Avro Schema

Review generated .avsc Avro schema, copy to clipboard, or export as a .avsc file.

JSON Schema to Apache Avro Conversion example

Converts JSON Schema User model into a strongly typed Avro record schema with timestamp-millis logical type, nullable union types, and default null attributes.

JSON Schema Definition Source
{
  "title": "User",
  "type": "object",
  "required": ["id", "username"],
  "properties": {
    "id": { "type": "integer", "format": "int64" },
    "username": { "type": "string" },
    "createdAt": { "type": "string", "format": "date-time" },
    "bio": { "type": "string" }
  }
}
Generated Apache Avro Schema (.avsc) Processed
{
  "type": "record",
  "name": "User",
  "namespace": "com.example",
  "fields": [
    {
      "name": "id",
      "type": "long"
    },
    {
      "name": "username",
      "type": "string"
    },
    {
      "name": "createdAt",
      "type": [
        "null",
        {
          "type": "long",
          "logicalType": "timestamp-millis"
        }
      ],
      "default": null
    },
    {
      "name": "bio",
      "type": [
        "null",
        "string"
      ],
      "default": null
    }
  ]
}

Technical Specifications & Engine Details

Technical specifications and engine details for JSON Schema to Apache Avro Converter
Specification Details
Supported Formats APPLICATION/JSON, APPLICATION/SCHEMA+JSON, TEXT/PLAIN, .JSON → APPLICATION/JSON, APPLICATION/AVRO, TEXT/PLAIN, .AVSC
Execution Mode 100% Client-Side In-Browser (client)
Browser Requirements Modern browser with JavaScript enabled.
Performance Constraints Runs client-side in browser memory. Performance and file limits are bounded by available local device RAM.
Maintained by Pragyan Pahadi

100% Client-Side Privacy Guarantee

Your files remain strictly on your local device. Zero data is transmitted to external servers.

Frequently Asked Questions

Are my JSON schemas uploaded to an external server?
No. All schema parsing and Avro transpilation run 100% locally in your web browser. Your private schema definitions, field names, and structures never leave your local device.
How are optional fields represented in Avro?
Properties that are not listed in the JSON Schema required array are automatically converted into Avro union types ["null", type] with a default value of null.
Which JSON Schema drafts are supported?
The converter supports Draft-04, Draft-06, Draft-07, Draft 2019-09, and Draft 2020-12 specifications.
How are date-time format strings converted in Avro?
When logical types are enabled, date-time format strings map to long with logicalType: "timestamp-millis", ensuring compatibility with Kafka and Avro tooling.

Methodology

This tool runs entirely in your browser. The example above shows a representative input and the result it produces.

Last updated .