Upload data and create table in Databricks SQL

The Databricks SQL create table UI allows you to quickly upload a CSV or TSV file and create a Delta table.

Types of target tables

Create table in Databricks SQL creates managed Delta tables in the Hive Metastore.


  • You need USAGE and CREATE permissions on the schema you want to create a table in.

  • You must have a running SQL Warehouse.

Create a table using file upload

You can use the UI to create a Delta table by importing small CSV or TSV files to Databricks SQL from your local machine.

  • The upload UI supports uploading a single file at a time under 100 megabytes.

  • The file must be a CSV or TSV and have the extension “.csv” or “.tsv”.

  • Compressed files such as zip and tar files are not supported.

Upload the file

  1. Navigate to the SQL persona by using the persona switcher.

    • To change the persona, click the icon below the Databricks logo Databricks logo, and select a persona.

  2. Click create button Create in the sidebar and select Table from the menu.

  3. The Create table in Databricks SQL page appears.

    Create table in DBSQL
  4. To start an upload, click the file browser button or drag-and-drop files directly on the drop zone.

    Uploading files


Imported files are uploaded to a secure internal location within your account which is garbage collected daily.

Table name selection

Upon completion of upload, you can select the destination for your data.

Table name selection
  1. Select a schema.

  2. By default, the UI converts the file name to a valid table name. You can edit the table name.

Data preview

After the file upload is complete, you can preview the data (limit of 50 rows).

  • After the upload, the UI tries to start the endpoint selected in the top right. You can switch endpoints at any time, but the preview and table creation require an active endpoint. If your endpoint is not active yet, it starts automatically. This may take some time. The preview starts when your endpoint is running.

Data preview
  • There are two ways to preview the data, vertically or horizontally. To switch between preview options, click the toggle button above the table view toggle.

Format options

Depending on the file format uploaded, different options are available. Common format options appear in the header bar, while less commonly used options are available in the Advanced attributes modal.

  • For CSV, the following options are available.

    • First row contains the header (enabled by default): This option specifies whether the CSV/TSV file contains a header.

    • Column delimiter: The separator character between columns. Only a single character is allowed, and backslash is not supported. This defaults to comma for CSV files.

    • Automatically detect column types (enabled by default): Automatically detect column types from file content. You can edit types in the preview table. If this is set to false, all column types are inferred as STRING.

    • Rows span multiple lines (disabled by default): Whether a column’s value can span multiple lines in the file.

The data preview updates automatically when you edit format options.

Column headers and types

You can edit column header names and types. Column header

  • To edit types, click the icon with the type.

  • To edit the column name, click the input box at the top of the column.

    • Column names do not support commas, backslashes, or unicode characters (such as emojis).

For CSV files, the column data types are inferred by default. You can interpret all columns as STRING type by disabling Advanced attributes > Automatically detect column types.


  • Schema inference does a best effort detection of column types. Changing column types may lead to certain values being cast to NULL if the value cannot be cast correctly to the target data type. Casting BIGINT to DATE or TIMESTAMP columns is not supported. Databricks recommends that you create a table first and then transform these columns using SQL functions afterwards.

  • To support table column names with special characters, create table UI via upload in Databricks SQL leverages Column Mapping.

  • To add comments to columns, create the table and navigate to Data Explorer where you can add comments.

Supported data types

Create table using CSV upload supports the following data types. For more information about individual data types see SQL data types.

Data Type



8-byte signed integer numbers.


Boolean (true, false) values.


Values comprising values of fields year, month, and day, without a time-zone.


8-byte double-precision floating point numbers.


Character string values.


Values comprising values of fields year, month, day, hour, minute, and second, with the session local timezone.

Creating the table

To create the table, click Create at the bottom of the page. Create table

After you create the table using Create table in Databricks SQL, the Data Explorer page for the Delta table under the designated catalog and schema appears.

Known issues

  • Casting BIGINT to non-castable types like DATE, such as dates in the format of ‘yyyy’, may trigger errors.