Connect Nuclino and Neo4j to Build Intelligent Automations
Enable Integrations or automations with these events of Nuclino and Neo4j
Enable Integrations or automations with these events of Nuclino and Neo4j
Triggers
New or Updated Items
Retrieve items from the selected Nuclino workspace that were created or modified since the last check.
New Items
Retrieve items created in the selected workspace within the specified recent time window.
Actions
Create an Item
Create a new item or collection in a Nuclino workspace. Optionally provide a title and content; returns the created object's details and URL.
Update Item
Update a Nuclino item's title and/or content using its Item ID.
Delete Item
Permanently deletes a Nuclino item specified by its Item ID.
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Frequently Asked Questions
To start, connect both your Nuclino and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Nuclino triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Nuclino 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 Nuclino 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 Nuclino 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 Nuclino
Nuclino is a collaborative platform designed to help teams organize and share knowledge efficiently. It offers a seamless way to create, manage, and collaborate on documents and projects in real-time, enhancing team productivity and communication.
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About 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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