Connect Capgo and Neo4j to Build Intelligent Automations
Enable Integrations or automations with these events of Capgo and Neo4j
Enable Integrations or automations with these events of Capgo and Neo4j
Triggers
New Organizaition
Triggers when a new organization is created.
New App
Triggers when a new app is created.
Actions
Update an Organization
Update an existing organization.
Create an Organization
Create a new organization.
Delete an Organization
Delete an existing organization.
Get All Members
Get all members of an organization.
Get Statistics
Get statistics for a specific organization.
Create a channel
Create a channel configuration.
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Frequently Asked Questions
To start, connect both your Capgo and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Capgo triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Capgo 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 Capgo 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 Capgo 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 Capgo
Capgo is a cutting-edge platform designed to enhance the capabilities of mobile app developers by providing real-time updates and seamless deployment solutions. It streamlines the process of managing and updating mobile applications, ensuring that users always have access to the latest features and improvements without the need for traditional app store updates.
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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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