Connect IronWiFi and Neo4j to Build Intelligent Automations
Enable Integrations or automations with these events of IronWiFi and Neo4j
Enable Integrations or automations with these events of IronWiFi and Neo4j
Triggers
New User
Triggers if a new user is created within scheduled time.
Actions
Create an User
Creates a new user
Create Group
Creates group with the specified name.
Generate Voucher
Generates the specified voucher.
Add Voucher
Add the specified voucher.
Add Attribute
Add attribute
Add Units
Add the specified unit.
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Frequently Asked Questions
To start, connect both your IronWiFi and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in IronWiFi triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how IronWiFi 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 IronWiFi 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 IronWiFi 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 IronWiFi
Ironwifi is a robust platform that provides secure and reliable Wi-Fi authentication and network security solutions. It offers tools for managing and securing wireless networks, ensuring that only authorized users can access the network. With features like RADIUS authentication, Ironwifi helps businesses protect their network infrastructure and maintain data integrity.
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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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