Tablizer

Convert CSV to Avro Schema Online

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

What CSV is

CSV is a text file where each line is a row and commas separate the fields. There is no type system, no formatting and no second sheet. Every value is text until something downstream decides otherwise.

Almost every database, analytics tool and spreadsheet can read and write it, which is why exports default to it.

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 CSV to Avro Schema

Reading CSV means deciding three things the file does not state: which character separates fields, how quotes work, and what encoding the bytes are in. Tablizer sniffs the delimiter from the first few lines, handles quoted fields containing commas and newlines, and reads the file as UTF-8.

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 CSV to Avro Schema

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

Avro wants a type for each column, and CSV does not record one, so each column is typed from what its values look like. A column of digits that should stay text - a zip code, a phone number, a leading-zero id - is the usual thing to check afterwards.

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.

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.

CSV in
id,name,role,started,hours
007,Halima Yusuf,"Analyst, data",2024-03-15,38.5
012,"Jonah ""Jo"" Pryce",Engineer,2025-11-02,
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 CSV to Avro Schema?

Paste your CSV 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 does my CSV open with all the data in one column?

The file uses a delimiter your spreadsheet did not expect. Exports from European locales often use semicolons because the comma is the decimal separator there. Change the delimiter in the export options and the columns split correctly.

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.

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