Is there any tool which ServiceNow supports bulk data import/export/delete or querying data

[shivamjwell]

Is there any tool which ServiceNow supports for bulk data import/export/delete or querying data from any table or any metadata that can help make data operations quicker and smoother?

[Adithya Masetti · Accepted solution]

Best tools for bulk data operations in ServiceNow

If you're looking to manage large volumes of data in ServiceNow—whether it's importing, exporting, deleting, or querying—these built-in tools can help streamline the process:

Import/Export

• Import Sets: Useful for bulk importing data from CSV, Excel, or XML files. Use transform maps to map data into target tables.

• Export from List Views: You can export records directly to CSV, Excel, or XML using the list view.

• REST APIs: Use /api/now/table/{table_name} to query and export data programmatically.

Bulk Deletion

• Table Cleaner: Automatically removes old records based on retention rules (commonly used for logs).

• Fix Scripts: One-time scripts for deleting or updating large sets of records.

• Scheduled Jobs: Automate regular cleanup using GlideRecord scripts.

Querying Data

• List Filters: Quickly filter and find records directly from the UI.

• Reports: Useful for analysis and can be scheduled for regular exports.

• Background Scripts: Use GlideRecord for powerful backend queries, updates, and deletions.

Advanced Options

• IntegrationHub ETL: For structured data integration and transformation (requires Pro or Enterprise).

• Metadata Tables: Use tables like sys_dictionary and sys_db_object to explore schema and table configurations.

[Adithya Masetti · Accepted solution]

Best tools for bulk data operations in ServiceNow

If you're looking to manage large volumes of data in ServiceNow—whether it's importing, exporting, deleting, or querying—these built-in tools can help streamline the process:

Import/Export

• Import Sets: Useful for bulk importing data from CSV, Excel, or XML files. Use transform maps to map data into target tables.

• Export from List Views: You can export records directly to CSV, Excel, or XML using the list view.

• REST APIs: Use /api/now/table/{table_name} to query and export data programmatically.

Bulk Deletion

• Table Cleaner: Automatically removes old records based on retention rules (commonly used for logs).

• Fix Scripts: One-time scripts for deleting or updating large sets of records.

• Scheduled Jobs: Automate regular cleanup using GlideRecord scripts.

Querying Data

• List Filters: Quickly filter and find records directly from the UI.

• Reports: Useful for analysis and can be scheduled for regular exports.

• Background Scripts: Use GlideRecord for powerful backend queries, updates, and deletions.

Advanced Options

• IntegrationHub ETL: For structured data integration and transformation (requires Pro or Enterprise).

• Metadata Tables: Use tables like sys_dictionary and sys_db_object to explore schema and table configurations.

[Community Alums · Accepted solution]

Hi @shivamjwell ,

you can use Precision Bridge  tool ,Precision Bridge is a powerful and recommended tool in ServiceNow for handling complex or enterprise-level data operations. It supports bulk import, export, update, delete, and synchronization of large volumes of data, making it ideal for scenarios like data migrations, mass updates, or integration with external systems. One of its key strengths is the ability to apply transformation logic, data mapping, filtering, and scheduling, which adds flexibility and control over how data is handled. Precision Bridge is especially useful in modules like CSM, HRSD, FSM, and other areas where there are complex data relationships and a need for reliable, scalable data processing.

[shivamjwell]

Thanks for your response @Community Alums, I found this helpful.

[Community Alums]

Hi @shivamjwell ,

I'm pleased to know the information was helpful. Please feel free to reach out if you have any further questions, as I'm happy to collaborate. You can also find me on LinkedIn: https://www.linkedin.com/in/tejas1018/ Thank you again.