NinjaOne connector
Set up the NinjaOne connector in Kaivo: authentication, configuration, the 8 BigQuery tables it syncs, and answers to common questions.
NinjaOne connector pricing, tier and credits on kaivo.io
Kaivo is a fully managed data platform that syncs your NinjaOne data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your data from NinjaOne instead of moving it.
What is the NinjaOne connector
Section titled “What is the NinjaOne connector”Sync your NinjaOne RMM data into BigQuery with Kaivo to inventory devices and audit IT activity across your organisations.
| Category | Tech |
|---|---|
| Authentication | API key |
| Setup | Self-service |
Getting started with the NinjaOne connector
Section titled “Getting started with the NinjaOne connector”- Sign up for Kaivo and create a workspace.
- Connect your NinjaOne account.
- Choose which tables to sync.
- Wait for the initial sync to finish.
- Query your data in BigQuery or your favourite AI or BI tool.
Authenticating NinjaOne
Section titled “Authenticating NinjaOne”Authenticate with your API Key.
| Field | Description |
|---|---|
| API Key | |
| Generate an API token from the NinjaOne admin portal under Administration > API. |
|
Configuring the NinjaOne connector
Section titled “Configuring the NinjaOne connector”When you set up the connector, you provide:
| Field | Description |
|---|---|
| Start Date | |
| Any data before this date will not be fetched. |
|
Tables and columns synced from NinjaOne
Section titled “Tables and columns synced from NinjaOne”Kaivo syncs 8 tables from NinjaOne into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.
activities (20 columns)
| Column | Type | Description |
|---|---|---|
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
type |
STRING |
|
activity_result |
STRING |
|
activity_time |
FLOAT64 |
|
activity_type |
STRING |
|
data__message__code |
STRING |
|
data__message__params__app_user_email |
STRING |
|
data__message__params__app_user_id |
STRING |
|
data__message__params__app_user_name |
STRING |
|
data__message__params__ip |
STRING |
|
data__message__params__mfa |
STRING |
|
data__message__params__new_user_email |
STRING |
|
data__message__params__new_user_id |
STRING |
|
data__message__params__new_user_name |
STRING |
|
id |
FLOAT64 |
|
message |
STRING |
|
status |
STRING |
|
status_code |
STRING |
|
user_id |
FLOAT64 |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
automation_scripts (8 columns)
| Column | Type | Description |
|---|---|---|
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
active |
BOOL |
|
created_on |
FLOAT64 |
|
id |
FLOAT64 |
|
language |
STRING |
|
name |
STRING |
|
updated_on |
FLOAT64 |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
Subtable: automation_scripts__architecture
Section titled “Subtable: automation_scripts__architecture”| Column | Type | Description |
|---|---|---|
_kaivo_parent_id |
STRING |
Foreign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo. |
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
value |
STRING |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
Subtable: automation_scripts__operating_systems
Section titled “Subtable: automation_scripts__operating_systems”| Column | Type | Description |
|---|---|---|
_kaivo_parent_id |
STRING |
Foreign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo. |
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
value |
STRING |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
Subtable: automation_scripts__script_parameters
Section titled “Subtable: automation_scripts__script_parameters”| Column | Type | Description |
|---|---|---|
_kaivo_parent_id |
STRING |
Foreign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo. |
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
value |
JSON |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
groups (8 columns)
| Column | Type | Description |
|---|---|---|
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
description |
STRING |
|
created |
FLOAT64 |
|
id |
FLOAT64 |
|
name |
STRING |
|
shared |
BOOL |
|
updated |
FLOAT64 |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
locations (5 columns)
| Column | Type | Description |
|---|---|---|
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
id |
FLOAT64 |
|
name |
STRING |
|
organization_id |
FLOAT64 |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
organizations (6 columns)
| Column | Type | Description |
|---|---|---|
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
description |
STRING |
|
id |
FLOAT64 |
|
name |
STRING |
|
node_approval_mode |
STRING |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
policies (8 columns)
| Column | Type | Description |
|---|---|---|
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
description |
STRING |
|
id |
FLOAT64 |
|
name |
STRING |
|
node_class |
STRING |
|
node_class_default |
BOOL |
|
updated |
FLOAT64 |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
roles (8 columns)
| Column | Type | Description |
|---|---|---|
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
chassis_type |
STRING |
|
created |
FLOAT64 |
|
custom |
BOOL |
|
id |
FLOAT64 |
|
name |
STRING |
|
node_class |
STRING |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
software_products (7 columns)
| Column | Type | Description |
|---|---|---|
_kaivo_id |
STRING |
Primary key that uniquely identifies the row. Auto-generated by Kaivo. |
active |
BOOL |
|
id |
STRING |
|
installable |
BOOL |
|
product_name |
STRING |
|
vendor_name |
STRING |
|
_kaivo_extracted_at |
TIMESTAMP |
Timestamp that shows when the row was extracted. Auto-generated by Kaivo. |
How the NinjaOne sync works
Section titled “How the NinjaOne sync works”After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where NinjaOne supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won’t get duplicate rows.
Frequently asked questions
Section titled “Frequently asked questions”How long does the initial sync take for NinjaOne?
Section titled “How long does the initial sync take for NinjaOne?”It depends on how much history is in your NinjaOne account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they’re much faster.
Can I sync only some tables or columns?
Section titled “Can I sync only some tables or columns?”Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don’t select are never copied to your warehouse.
What happens when NinjaOne’s schema changes?
Section titled “What happens when NinjaOne’s schema changes?”New fields are never added automatically. You choose which fields to sync, so data you haven’t selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table’s sync mode: full-refresh tables always match what’s currently in NinjaOne, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.
How do I handle GDPR or data deletion requests?
Section titled “How do I handle GDPR or data deletion requests?”Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in NinjaOne instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the NinjaOne connector in Kaivo and all of its synced data is deleted with it.
Common use cases for NinjaOne data
Section titled “Common use cases for NinjaOne data”Device and org inventory
Section titled “Device and org inventory”Use organizations and groups to report on the devices you manage.
Activity audit
Section titled “Activity audit”Use activities to track management actions over time.
Software and policy view
Section titled “Software and policy view”Join software_products with policies to review configuration across devices.
Use NinjaOne data in your AI and BI tools
Section titled “Use NinjaOne data in your AI and BI tools”Once NinjaOne data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here’s how the most common destinations work with NinjaOne data.
Claude
Section titled “Claude”Use Kaivo’s MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →
Power BI
Section titled “Power BI”Microsoft’s BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →
Data Studio
Section titled “Data Studio”Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →
Tableau
Section titled “Tableau”The premium analytics standard, with native BigQuery integration. Setup guide →
Google Sheets
Section titled “Google Sheets”Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →
Connect via Power Query’s BigQuery connector. Setup guide →
Metabase
Section titled “Metabase”Open-source BI tool with strong BigQuery support. Setup guide →
See our pricing page for NinjaOne connector pricing and plan details.