Connect Outscraper and Neo4j to Build Intelligent Automations
Enable Integrations or automations with these events of Outscraper and Neo4j
Enable Integrations or automations with these events of Outscraper and Neo4j
Triggers
Task Finished
Triggers when a task is finished.
Actions
Google Search News
Fetch news results from Google News based on a specified query.
Google Search
Fetch real-time search results from Google based on specified queries.
Emails and Contacts
Find email addresses, social links, and phone numbers from domains.
Search for Places on Google Maps
Search for places on Google Maps be queries, links, google or places IDs
Email Address Verifier
Validate one or more email addresses to check if they are deliverable.
Google Maps Reviews
Fetch Google Maps reviews for places based on search queries.
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Frequently Asked Questions
To start, connect both your Outscraper and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in Outscraper triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how Outscraper 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 Outscraper 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 Outscraper 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 Outscraper
Outscraper is a service that allows you to scraper the data and reviews from Google Maps in real-time. Use simple queries and extract any amount of local businesses into JSON.
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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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