ETL from BigQuery as a Source to any target in a few clicks
- Build scalable, production-ready data pipelines in hours, not days
- Extract and load BigQuery as a Source data into any target without code
- Complete your entire ELT pipeline with SQL or Python transformations
How to get started with our BigQuery as a Source integration
See it in action
Put your BigQuery as a Source data to use.Deliver BigQuery as a Source data at the right time, to the right people.
Transform your data
Turn raw data into business data models with SQL or Python.
Activate your data
Sync data directly into your tech stack with reverse ETL.
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
Integrated Data Activation
Bring all your data together. Integrate data from anywhere
VP, Business Analytics & Platforms
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.