Connect Backlog and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Backlog
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of Backlog and Neo4j
Enable Integrations or automations with these events of Backlog and Neo4j
Actions
Get all Activities
Find all existing activities
Get Space Logo
Returns logo image of your space.
Get Space Notification
Returns space notification.
Get Space Disk Usage
Returns information about space disk usage.
Get all Projects
Find all existing projects
Get all Notifications
Find all existing notifications
Know More About Backlog and Neo4j Integrations
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Frequently Asked Questions
To start, connect both your Backlog and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Backlog triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Backlog data is recorded in Neo4j. This includes choosing which data fields go into which fields of Neo4j, setting up custom formats, and filtering out unwanted information.
The data sync between Backlog and Neo4j typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Backlog and Neo4j. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Backlog
Backlog is a comprehensive project management and collaboration tool designed to help teams organize their work, track progress, and collaborate effectively. It offers features such as task management, bug tracking, version control, and Gantt charts to streamline project workflows.
Learn MoreAbout Neo4j
Neo4j is a leading graph database platform that enables organizations to unlock the value of connections, influences, and relationships in data. It is designed to handle highly connected data and is used for a variety of applications such as fraud detection, real-time recommendations, and network management.
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