ETL from Webhook to Google Cloud Storage in a few clicks
- Leverage Webhook data in Google Cloud Storage for advanced analytics
- Build scalable, production-ready data pipelines in hours, not days
- Extract data from Webhook and load into Google Cloud Storage without code
- Complete your entire ELT pipeline with SQL or Python transformations
- Centralize Webhook data in Google Cloud Storage for unified access and analytics
How to get started with our Webhook to Google Cloud Storage integration
See Webhook to Google Cloud Storage in action
Ready-Made Data Model Starter Kits with Google Cloud Storage
Everything you need to simplify advanced data integration
Zero Infrastructure to Manage
Managed SQL/Python Modeling
Predictable Value-Based Pricing
Reduced Data Development Waste
No-Code Any Data Ingestion
Efficient Database Replication
Infinite Scale
Integrated Data Activation
Proactive Troubleshooting
Bring all your data together. Integrate data from anywhere
Greg Robinson
Staff Data Scientist
Load Webhook to any data lake or warehouse
FAQ
In order to receive data in real-time, a traditional API must poll for data constantly. Webhooks, on the other hand, enable applications to provide real-time data to other applications based on triggered events.
When an event occurs in an app – such as registering an account or purchasing an item – a webhook can immediately push this data to other apps via HTTP callbacks. This allows teams, applications, data models, and other parties to react to these events in real-time.
In Rivery, webhooks operate like any other data source. To facilitate webhooks, Rivery provides an endpoint that streams webhooks data. Customers utilize this endpoint by sending HTTP requests to it via the POST method.
While setting up a webhook data source, all Rivery customers need to do is provide example JSON mapping for the data. Auto-mapping will take care of the rest.
Once a webhook data source is activated, Rivery sends webhook events directly to a customer’s cloud data warehouse as they happen. Customers can push events one by one, or transfer records in bulk by sending an array.
The granular detail of webhook events, coupled with the instant accessibility, enables teams and data operations to react in real-time with the best possible data. Customers can also use this granularity to develop more powerful data models.
With Rivery Webhooks, customers can combine events data with other data sources inside a cloud data warehouse to generate unique insights.
Additionally, the feature serves as a comprehensive archive for all events that occur within an app. This is especially important for webhooks that do not permanently store events.
In Rivery, e-commerce customers can configure a Shopify webhook to execute a process after a specific event.
For example, when an order is placed, the webhook can trigger an email send to the buyer featuring product documentation or related items. Receiving automated updates from webhooks allows e-commerce companies to react to, and interact with, buyers in real-time.
Using Rivery’s data connectors is very straightforward. Just enter your credentials, define the target you want to load the data into (i.e. Snowflake, BigQuery, Databricks or any data lake and auto map the schema to generate on the target end. You can control the data you need to extract from the source and how often to sync your data. To learn more follow the specific docs.
Yes. All data connectors within Rivery comply with the highest security and privacy standards, including: GDPR, HIPPA, SOC2 and ISO 27001. In addition, when the data flows into your target data warehouse, you can configure it to do so via your own cloud files system vs. Rivery.
The most popular data connectors are for use cases like marketing, sales and finance. These include Salesforce, HubSpot, Google Analytics, Google Ads, LinkedIn Ads, Facebook Ads, TikTok and more.
Rivery supports both CDC database replication and Standard SQL extraction so you can choose the method that works best for you. Learn more here.