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  • Product
    • First-party trackingFirst-party tracking

      Powerful server-side solution for collect and connect customer data

    • Marketing ETLMarketing ETL

      Create secure customer’s data pipelines to any data warehouses

  • Resources
    • BlogBlog

      Stories on how to use customer data for company growth

    • DocumentationDocumentation

      Learn how to install, set up, and use Renta tools.

  • Pricing
  • Connectors
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Renta
Marketing ETL
PostgreSQL to Google BigQuery

ETL PostgreSQL data to Google BigQuery

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Free for 7 days. No credit card required.

Source
Destination
Renta ELT is a simple way to create data pipelines in minutes. Not months.
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PostgreSQL is a powerful open-source database trusted by businesses worldwide.
Renta Marketing ELT seamlessly moves your PostgreSQL data to Google BigQuery, enabling instant access to unified analytics for your marketing and product teams.
Enjoy automated, secure, and always up-to-date data flows designed for fast insights and confident decision-making.

Set up your ELT pipeline in 3 simple steps

Select PostgreSQL as your data source and securely authenticate your account to initiate the data extraction process.

Selecting PostgreSQL as the data source in Renta.
1Connect your source

Select PostgreSQL as your data source and securely authenticate your account to initiate the data extraction process.

Selecting PostgreSQL as the data source in Renta.
2Identify the destination
3Configure and synchronize
The data structure of the PostgreSQL API

Renta supports 7 methods of data export using the PostgreSQL API.

Tables

Represents the core data storage units in PostgreSQL, containing structured data organized in rows and columns. Each table defines a schema for storing records of a specific entity.

Views

Virtual tables that present data from one or more tables through a predefined SQL query, enabling simplified data access and abstraction without duplicating data.

Schemas

Logical containers that group related database objects such as tables, views, and functions, supporting organization, access control, and namespace management within a database.

Indexes

Specialized data structures that improve query performance by enabling faster data retrieval on specified columns within tables.

Functions

Reusable routines written in SQL or procedural languages that perform operations or calculations, often used to encapsulate business logic or data transformations.

Sequences

Database objects that generate unique numeric values, typically used for auto-incrementing primary keys in tables.

Triggers

Procedures that are automatically executed in response to specific events on a table or view, such as insertions, updates, or deletions, enabling automation and data integrity enforcement.

Use cases

Unlock actionable PostgreSQL insights

  • Sync transactional data to BigQuery for real-time revenue and churn analysis
  • Blend website event logs with sales data to optimize lead conversion strategies
  • Aggregate product usage metrics to identify upsell opportunities by customer segment
  • Automate marketing attribution by merging campaign data from PostgreSQL and BigQuery
  • Enable cross-platform cohort analysis by unifying user data from both sources
  • Monitor inventory trends by combining order data with supply chain analytics in BigQuery
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Use cases: PostgreSQL and Google BigQuery integration
TEMPLATES

Start quickly with these use case templates

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Frequently asked questions
Reliable data ingestion for your Modern Data Stack

Free for 7 days. No credit card required.

Automate extraction from 100+ connections. 99.9% Uptime SLA.

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  • Marketing ETL
  • First-party data streaming
Popular connectors
  • Salesforce → Bigquery
  • Google Ads → Bigquery
  • Facebook Ads → Bigquery
  • Facebook Ads → Snowflake
  • Google Sheets → Bigquery
  • Google Sheets → Snowflake
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