Connect splitwise and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
New Expense
New Group
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of splitwise and Neo4j
Enable Integrations or automations with these events of splitwise and Neo4j
Triggers
New Expense
Triggers when a new expense is added to a group or with friends.
New Group
Triggers when a new group is created.
Actions
Create Expense
Create Group
Creates a new group
Delete Expense
List Current User's Expenses
List all the current user's expenses.
Delete Group
Add user to group
Know More About Splitwise and Neo4j Integrations
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Frequently Asked Questions
To start, connect both your splitwise and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in splitwise triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how splitwise 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 splitwise 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 splitwise 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 splitwise
Splitwise is a platform designed to help users manage and share expenses with friends, family, and roommates. It simplifies the process of tracking shared bills and IOUs, ensuring everyone pays their fair share. Ideal for group trips, shared households, and any situation where expenses need to be divided among multiple people.
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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