Connect Zakeke and Neo4j to Build Intelligent Automations
Enable Integrations or automations with these events of Zakeke and Neo4j
Enable Integrations or automations with these events of Zakeke and Neo4j
Triggers
New Marketplace Order Item
Triggers when a new a new order item is created for an order coming from a marketplace (such as Etsy) or from a manual order.
New Order Item
Triggers when a new customized order is received and print-ready files are generated.
Actions
Retrieve an order by ID
Retrieve existing an order by ID.
Get an order by code
Retrieve an order by code.
Retrieve a design by ID
Retrieve relevant data about a design.
Retrieve print-ready file with a given file format
Retrieve print-ready file with a given file format.
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Frequently Asked Questions
To start, connect both your Zakeke and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Zakeke triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Zakeke 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 Zakeke 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 Zakeke 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 Zakeke
Zakeke is a powerful platform that enables businesses to offer product customization and 3D visualization to their customers. It integrates seamlessly with e-commerce platforms, allowing users to personalize products in real-time, enhancing the shopping experience and boosting sales.
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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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