Add Data to Database

Learn how to add, import, and manage data in your CodeNull database

Adding Data to Your Database

After creating your database, the next step is to populate it with data. CodeNull provides several methods to add and manage data in your database without writing complex database queries.

Methods for Adding Data

Manual Entry

Create records one at a time through the interface

Bulk Import

Import data from CSV, Excel, JSON, or other formats

AI Generation

Generate sample data using AI for testing

API Integration

Connect to external data sources via APIs

Form Submissions

Create frontend forms that add data to your database

Data Migration

Transfer data from another database

Manual Data Entry

The Data Explorer interface allows you to create individual records manually:

1. Open Collection/Table

   In your database dashboard, click on the collection or table where you want to add data.

2. Create New Record

   Click the “Add Record” button in the top-right corner of the Data Explorer.

3. Enter Field Values

   Complete the form with values for each field in your collection/table schema.
4. Validate and Save

   Click “Validate” to check for any errors, then “Save” to add the record to your database.

When entering data manually, you can use the “Clone” button to create similar records quickly. This is useful when adding multiple records with slight variations.

Bulk Data Import

For adding multiple records at once, use the Bulk Import feature:

1. Access Import Tool

   From your collection/table view, click “Import” in the toolbar.

2. Select Import Method

   Choose your data source:

   • Upload a file (CSV, Excel, JSON)
   • Paste data (JSON, CSV format)
   • Connect to external source
3. Configure Mapping

   Map the imported data fields to your database schema fields.

   For each imported column, you can:

   • Match to an existing field
   • Transform data during import
   • Skip certain columns
   • Handle special data types (dates, geo coordinates, etc.)
4. Validation Options

   Configure how to handle validation issues:

   • Skip invalid records
   • Attempt to fix common issues
   • Stop import on any error
   • Create a validation report
5. Execute Import

   Click “Start Import” to begin the process. A progress indicator will show the status.

6. Review Results

   After import completes, review the summary showing:

   • Number of records imported successfully
   • Any validation issues encountered
   • Fields that required transformation

AI-Generated Test Data

CodeNull can generate realistic test data based on your schema:

1. Access AI Data Generator

   From your collection/table view, click “Tools” → “Generate Test Data”.

2. Configure Generator

   Set parameters for your test data:

   • Number of records to generate
   • Value ranges and patterns
   • Relationships between records
   • Scenarios to simulate (e.g., e-commerce transactions)
3. Preview Generated Data

   Review a sample of the data that will be generated and adjust settings as needed.

4. Generate and Import

   Click “Generate” to create the test data and add it to your database.

Form-Based Data Collection

To collect data from users through your application:

1. Create Form in Frontend

   Use the Frontend Dashboard to create a form component connected to your database.

2. Configure Data Mapping

   Map form fields to database fields, including validation rules.

3. Set Up Form Processing

   Configure what happens when the form is submitted:

   • Direct database entry
   • API processing before storage
   • Email notifications
   • Confirmation messages
4. Test Form Submission

   Test the form to ensure data is correctly saved to your database.

Managing Existing Data

CodeNull provides tools to work with your existing data:

Data Explorer Interface

The Data Explorer allows you to:

• Browse records with filtering and sorting
• Edit individual field values
• Delete or archive records
• Export selected records
• View data relationships

Batch Operations

Perform operations on multiple records at once:

• Update field values across many records
• Delete records matching certain criteria
• Export filtered data sets
• Run data transformations

Batch Update Example

To update a field across multiple records:

1. Use filters to select the target records
2. Click “Batch Update” in the toolbar
3. Select the field to update
4. Enter the new value or transformation rule
5. Preview changes before applying
6. Confirm to update all matching records

Conditional Batch Delete

To delete records matching specific criteria:

1. Create a filter for the records to delete
2. Click “Batch Delete” in the toolbar
3. Review the affected records count
4. Choose between hard delete or soft delete (archive)
5. Confirm deletion with any required verification

Best Practices

Start with a small set of test data to verify your schema design before importing large datasets.

• Use descriptive IDs: Create readable identifiers for important records
• Validate before import: Check data quality before adding to your database
• Document data sources: Track where your data came from for future reference
• Test with realistic data: Use data that resembles production use cases
• Backup before bulk operations: Create database backups before large data changes

Next Steps

After adding data to your database, explore these next steps:

• Design and optimize your database schema
• Set up data migration workflows
• Connect your database to frontend components