Connect Nifty and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Nifty
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of Nifty and Neo4j
Enable Integrations or automations with these events of Nifty and Neo4j
Actions
Create Task
Creates a new task in a specific project or workspace.
Create Project
Creates a new project within an organization or team.
Create Milestone
Creates a new milestone to track project progress.
Search User Details
This endpoint fetch the user information.
Create Portfolio
creates new portfolio
Create Document
creates a new document.
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Frequently Asked Questions
To start, connect both your Nifty and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Nifty triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Nifty 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 Nifty 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 Nifty 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 Nifty
Nifty is a project management and team collaboration tool designed to streamline your workflow and enhance productivity. It offers features such as task management, time tracking, project timelines, and team communication to help you manage your projects efficiently.
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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