Convert SQL to Avro Schema Online

Paste a SQL 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.

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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 SQL is

SQL here means the statements that move a table into a database: INSERT INTO with a VALUES list, and optionally the CREATE TABLE that defines the columns.

Anyone seeding a database, moving a spreadsheet into an application, or writing a migration.

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 SQL to Avro Schema

Column names come from the INSERT column list, or from a CREATE TABLE if one is present. Quoted strings are unquoted, doubled quotes are collapsed, and NULL becomes an empty cell.

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 SQL to Avro Schema

One property of the SQL has no home in Avro, and it is worth knowing which before you convert.

Avro has no header row. The column names are repeated as keys on every record instead, which is why the result is bigger on disk than the table it came from.

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.

SQL in

INSERT INTO `staff` (`id`, `name`, `role`, `started`, `hours`) VALUES
  ('007', 'Halima Yusuf', 'Analyst, data', '2024-03-15', '38.5'),
  ('012', 'Jonah "Jo" Pryce', 'Engineer', '2025-11-02', NULL),
  ('104', 'Wei Chen', 'Manager', '2023-06-30', '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 SQL to Avro Schema?

Paste your SQL 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.

Are the generated INSERT statements safe to run?

Quotes in your data are escaped, so the statements are syntactically correct. They are not parameterised, which is fine for a one-off import you are running yourself and not fine as a pattern for application code that takes user input.

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.