Convert YAML to Avro Schema Online

Paste a YAML table below, edit it if you need to, and get Avro Schema back. The conversion runs in your browser, so nothing is uploaded, there is no size limit and there is no signup.

From

From a page

The only part of this site that uses a server. The address is sent to it so the page can be fetched, because a browser is not allowed to fetch someone else's page itself. Your own files are never involved.

Nothing here is uploaded. The parsing happens on this page.

Edit

Paste or upload something above and it will appear here.

ToDataMarkupDocumentsCodeSchemasImages

Header rowDetect numbers

The output will appear here once there is a table to convert.

What YAML is

YAML uses indentation instead of brackets. It is a superset of JSON, supports comments, and is meant to be edited by hand.

Kubernetes manifests, CI pipelines, Ansible playbooks and most modern config files.

What Avro Schema is

An Avro schema describes a record: its name and its typed fields. It is the contract, not the data.

Kafka pipelines and anything in the Hadoop family.

What changes when you convert YAML to Avro Schema

A YAML list of maps reads as rows and columns directly. Anchors and aliases are resolved before the table is built, so a repeated block arrives expanded rather than as a reference.

Types are inferred per column from the values present. Any column with a gap in it becomes a union with null, because a reader rejects a record whose non-nullable field is missing.

What carries over from YAML to Avro Schema

Avro can express everything YAML holds about a table, so this conversion is about shape rather than loss.

The result can be read a record at a time, and appended to by adding to the end of it. That is worth having for a table too large to hold in memory, and it means a Avro file that is cut off part way through still gives you every record before the cut.

Both formats record types, so numbers, booleans and nulls survive as themselves rather than as text.

A worked example

Three rows of staff data, with an identifier that has a leading zero, a value containing a comma, a value containing quotes and one blank cell. Those are the four places formats disagree, so they are the four places to look.

YAML in

- id: "007"
  name: Halima Yusuf
  role: Analyst, data
  started: "2024-03-15"
  hours: "38.5"
- id: "012"
  name: Jonah "Jo" Pryce
  role: Engineer
  started: "2025-11-02"
  hours: ""
- id: "104"
  name: Wei Chen
  role: Manager
  started: "2023-06-30"
  hours: "40"

Avro Schema out

{
  "type": "record",
  "name": "staff",
  "fields": [
    {
      "name": "id",
      "type": "long"
    },
    {
      "name": "name",
      "type": "string"
    },
    {
      "name": "role",
      "type": "string"
    },
    {
      "name": "started",
      "type": "string"
    },
    {
      "name": "hours",
      "type": [
        "null",
        "double"
      ]
    }
  ]
}

Questions

How do I convert YAML to Avro Schema?

Paste your YAML into the box above or drop the file onto it. Check the table in the grid, then copy or download the Avro Schema from the output panel. It takes one step and the data never leaves your browser.

Why did my YAML value change meaning?

YAML reads several bare words as booleans. In the 1.1 spec that includes yes, no, on and off, which is why a country column containing NO for Norway can arrive as false. Quote values you want kept as text.

Is there a limit on file size?

No. The work happens on your own machine, so the limit is your machine's memory rather than an upload cap. A file with tens of thousands of rows converts in a second or two.

Is my data uploaded anywhere?

No. The parsing and generating are done by JavaScript running on this page. You can watch the network tab while you convert and see that nothing is sent.