Tables

Tables let you store and manage structured data directly in your workspace, organized into databases. Use them to maintain reference data, collect workflow outputs, or build lightweight data stores — all without leaving SteelEngine.

Each table has a schema of typed columns, supports filtering and sorting, and is fully accessible through the Tables API.

Creating a Table

1. Open the Databases section from your workspace sidebar
2. Open the database that should contain the table, or create one with New database
3. Click New table
4. Name your table and start adding columns

Table names must be unique within their database. Tables start with a single text column. Add more columns by clicking New column in the column header area.

Column Types

Each column has a type that determines how values are stored and validated.

Working with Rows

Adding Rows

• Click New row below the last row to append a new row
• Press Shift + Enter while a cell is selected to insert a row below
• Paste tabular data (from a spreadsheet or TSV) to bulk-create rows

Editing Cells

Click a cell to select it, then press Enter, F2, or start typing to edit. Press Escape to cancel, or Tab to save and move to the next cell.

Selecting Rows

Click a row's checkbox to select it. Selecting additional checkboxes adds to the selection without clearing previous selections.

Deleting Rows

Right-click a selected row (or group of selected rows) and choose Delete row from the context menu.

Import from CSV

Create a table from a spreadsheet export instead of building it by hand:

1. Open the database that should contain the table
2. Click Upload CSV in the header and choose one or more .csv or .tsv files (up to 50 MB each)

Each file becomes a table named after the file. The header row becomes the columns. SteelEngine normalizes column names to letters, numbers, and underscores. It infers each column's type (Text, Number, Boolean, or Date) from the first 100 rows and falls back to Text. The new table gets the row cap of your plan. If the import fails, for example because the file has more rows than the cap allows, SteelEngine removes the partly created table.

Column names that collide after normalization receive numbered suffixes, ignoring case: Contact Name and Contact-Name become Contact_Name and Contact_Name_2. Uploads and imports through Chat use the same normalization and type inference.

Appending a File to an Existing Table

Chat and MCP can append a workspace file to an existing table using steelengine_tables.import_file. Supported files are CSV, TSV, and JSON arrays of objects. Values are converted to the existing column types; only matching columns are imported.

Imports recognize exact column names, current normalized names, and the trailing-underscore names created by older assistant imports. If those conventions would send values to different columns, the import stops with Ambiguous file column mapping before inserting rows. Rename the file's headers to the exact target table column names, then retry.

Relationships Between Tables

A relationship links a column in one table to a column in another table of the same workspace. A cell can then point at a row instead of repeating its data. Open a table and click Relations in the header to see its relations or create one.

1. Pick the other table under Create a relation
2. Choose the direction: Many-to-one (many records here share one record there) or One-to-many (one record here contains many records there)
3. Map the two join columns. The column on the "many" side stores the reference. It must have the same type as the column it points at, and it cannot be the row ID
4. Review the Sample matches preview and click Create relation

The relation column shows the matched row instead of a raw value. The table on the "one" side gains a read-only overlay column that lists the rows pointing at each of its rows. Creating a relation does not modify existing rows. SteelEngine blocks the deletion of a row while other rows still point at it. Deleting a table removes its relations.

Archiving and Restoring Tables

Table deletion and database deletion have separate rules. Tools can delete tables with the required permission and confirmation. Deleting the containing database requires an empty database and a signed-in dashboard action; see Deleting a Database.

Deleting a table (Delete in its context menu) archives it rather than removing it. Archived tables disappear from the database and from table lists. You can restore one from Settings → Recently Deleted under Tables. A restored table returns to its database, or to the Default database if its own was deleted. If another table has taken its name, SteelEngine adds a suffix to the restored name. The Database block's List Tables operation can include archived tables when you set Table Status to Archived or All.

Filtering and Sorting

Use the toolbar above the table to filter and sort your data.

• Filter: Set conditions on any column (e.g., "Name contains Acme"). Multiple filters are combined with AND logic.
• Sort: Order rows by any column, ascending or descending.

Filters and sorts are applied in real time and do not modify the underlying data.

Keyboard Shortcuts

All shortcuts work when the table is focused and no cell is being edited.

Navigation

Selection

Editing

Clipboard

History

Using Tables in Workflows

Tables can be read from and written to within your workflows using the Table block. Common patterns include:

• Lookup: Query a table for reference data (e.g., pricing rules, customer metadata)
• Write-back: Store workflow outputs in a table for later review or reporting
• Iteration: Process each row in a table as part of a batch workflow

API Access

Tables are fully accessible through the REST API. You can create, read, update, and delete both tables and rows programmatically.

See the Tables API Reference for endpoints, parameters, and examples.

Permissions

Table access follows catalog permissions. The seeded Viewer role grants table:read, table:query, and table:export. The seeded Editor role adds table:create, table:update, table:delete, table:manage_schema (adding, changing, and removing columns), and table:import (CSV import). Custom roles can grant any subset — see Roles and Permissions.

Limits

Limits are per workspace, set by the workspace's billing plan:

Self-hosted deployments with billing disabled give every workspace the Enterprise limits.

Additional structural limits apply regardless of plan:

• 50 databases per workspace
• 1,000 columns per table
• 100 KB per row
• 100 KB per text value (the row size is the binding limit)
• 1,000 rows per batch insert / bulk update / bulk delete
• 1,000 rows per query result (default 100)

Best Practices

• Use typed columns to enforce data integrity — prefer Number and Boolean over storing everything as Text
• Name columns descriptively so they are self-documenting when referenced in workflows
• Use JSON columns sparingly — they are flexible but harder to filter and sort against
• Leverage the API for bulk imports rather than manually entering large datasets