Stream data from Google Analytics V4 Data API to PostgreSQL
Move data from Google Analytics V4 Data API to PostgreSQL in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.
- No credit card required
- 30-day free trial


- 200+Of connectors
- 5500+Active users
- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate Google Analytics V4 Data API with PostgreSQL in 3 simple steps
Connect Google Analytics V4 Data API as your data source
Set up a source connector for Google Analytics V4 Data API in minutes. Estuary supports streaming (including CDC where available) and batch data capture through events, incremental syncs, or snapshots — without custom pipelines, agents, or manual configuration.
Configure PostgreSQL as your destination connector
Estuary supports intelligent schema handling, with schema inference and evolution tools that help align source and destination structures over time. It supports both batch and streaming data movement, reliably delivering data to PostgreSQL.
Deploy and Monitor Your End-to-End Data Pipeline
Launch your pipeline and monitor it from a single UI. Estuary guarantees exactly-once delivery, handles backfills and replays, and scales with your data — without engineering overhead.

Google Analytics V4 Data API connector details
The Google Analytics Data API connector syncs data from Google Analytics 4 (GA4) properties into Estuary collections using the GA4 Data API. It delivers dependable, right-time visibility into website and app engagement metrics.
- Comprehensive coverage: Capture data on active users, devices, pages, traffic sources, and locations, or define custom GAQL-style reports.
- Right-time sync cadence: Incremental updates (default: every 12 hours) keep dashboards current without exceeding API limits.
- Custom reporting: Build tailored collections with flexible dimensions, metrics, and filters, including total and max aggregations.
- Secure setup: Connect via OAuth or service credentials for automated access.
- Smart lookback window: Configure up to 30 days to capture delayed or revised GA4 data.
💡 Data freshness: Right-time polling (periodic incremental sync) — reliable GA4 reporting with flexible interval control.

PostgreSQL connector details
Optimized for analytical and transactional workloads, the Estuary PostgreSQL connector materializes Flow collections into tables within PostgreSQL databases in real time. It creates and manages tables automatically, ensuring low-latency writes and schema consistency. The connector supports self-hosted, RDS, Aurora, Cloud SQL, Azure Database for PostgreSQL, and Supabase, with secure connectivity through SSL or SSH tunneling.
- Real-time data materialization into PostgreSQL tables
- Works with managed and on-prem PostgreSQL environments
- Supports delta updates and schema management
- Automatically handles table creation and reserved words
- Secure connections via SSL and SSH
Spend 2-5x less
Estuary customers not only do 4x more. They also spend 2-5x less on ETL and ELT. Estuary's unique ability to mix and match streaming and batch loading has also helped customers save as much as 40% on data warehouse compute costs.

Google Analytics V4 Data API to PostgreSQL pricing estimate
Estimated monthly cost to move 800 GB from Google Analytics V4 Data API to PostgreSQL is approximately $1,000.
Data moved
Choose how much data you want to move from Google Analytics V4 Data API to PostgreSQL each month.
GB
Choose number of sources and destinations.
Why pay more?
Move the same data for a fraction of the cost.



Estuary in action
See how to build end-to-end pipelines using no-code connectors in minutes. Estuary does the rest.
What customers are saying
Why Estuary is the best choice for data integration
Estuary combines streaming and batch data movement capabilities into a unified modern data pipeline. This approach simplifies building and operating pipelines like Google Analytics V4 Data API to PostgreSQL without custom code or orchestration.

Increase productivity 4x
With Estuary companies increase productivity 4x and deliver new projects in days, not months. Spend much less time on troubleshooting, and much more on building new features faster. Estuary decouples sources and destinations so you can add and change systems without impacting others, and share data across analytics, apps, and AI.
Getting started with Estuary
Free account
Getting started with Estuary is simple. Sign up for a free account.
Sign upDocs
Make sure you read through the documentation, especially the get started section.
Learn moreCommunity
I highly recommend you also join the Slack community. It's the easiest way to get support while you're getting started.
Join Slack CommunityEstuary 101
I highly recommend you also join the Slack community. It's the easiest way to get support while you're getting started.
Watch

Frequently Asked Questions
Is this integration suitable for production workloads?
Yes. Estuary pipelines are designed for production use, with exactly-once delivery semantics, automated backfills, and continuous operation at scale.
Can I control where my data runs and is processed?
Yes. Estuary offers multiple deployment options, including fully managed SaaS, private deployments, and bring-your-own-cloud (BYOC). This allows teams to control where their data plane runs and meet security, compliance, and networking requirements. Learn more about Estuary's security and deployment options.
Can I build this Google Analytics V4 Data API to PostgreSQL integration manually?
Yes, it's possible to build a manual pipeline using custom scripts, scheduled jobs, or open-source tools. However, manual approaches typically require ongoing maintenance, custom error handling, schema management, and operational overhead. Estuary simplifies this by providing a managed pipeline with built-in reliability, scaling, and monitoring.
Related integrations with Google Analytics V4 Data API
DataOps made simple
Add advanced capabilities like schema inference and evolution with a few clicks. Or automate your data pipeline and integrate into your existing DataOps using Estuary's rich CLI.




































