Stream data from PostgreSQL to PostgreSQL
Move data from PostgreSQL to PostgreSQL in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.
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- 30-day free trial
- 200+Of connectors
- 5500+Active users
- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate PostgreSQL with PostgreSQL in 3 simple steps
Connect PostgreSQL as your data source
Set up a source connector for PostgreSQL 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.
PostgreSQL connector details
Built for real-time data integration, the Estuary PostgreSQL connector streams inserts, updates, and deletes from PostgreSQL databases using Change Data Capture (CDC) via logical replication. It reads directly from the write-ahead log (WAL) to deliver low-latency, exactly-once data movement into Estuary collections. The connector supports self-hosted, RDS, Aurora, Cloud SQL, Azure Database for PostgreSQL, and Supabase, with secure connectivity options such as SSH tunneling and SSL.
- Continuous CDC streaming through PostgreSQL logical replication
- Works with managed and on-prem PostgreSQL instances
- Supports backfill and read-only captures
- Automatically manages replication slots and publications
- Secure setup via SSH or SSL
See how Curri uses PostgreSQL
PostgreSQL connector details
The PostgreSQL materialization connector writes Estuary collections into PostgreSQL tables and keeps them updated continuously as source data changes. Estuary creates and manages destination tables for each selected collection, applies ongoing inserts, updates, and deletes, and maintains schema consistency so PostgreSQL can serve real-time application, reporting, and operational workloads.
- Materialize Estuary collections into PostgreSQL tables with low-latency, incremental updates.
- Create and manage destination tables automatically based on your selected Estuary collections.
- Apply inserts, updates, and deletes so PostgreSQL stays current with upstream source changes.
- Connect using your PostgreSQL host, port, database name, schema, and database user credentials.
- Use port 5432 by default when no custom port is specified.
- Support self-hosted PostgreSQL, Amazon RDS, Amazon Aurora, Google Cloud SQL, Azure Database for PostgreSQL, and Supabase.
- Use SSL, SSH tunneling, or cloud IAM authentication where supported for secure connectivity.
- Handle schema evolution, table naming, and reserved words during materialization.
Estuary in action
See how to build end-to-end pipelines using no-code connectors in minutes. Estuary does the rest.
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.
PostgreSQL to PostgreSQL pricing estimate
Estimated monthly cost to move 800 GB from PostgreSQL to PostgreSQL is approximately $1,000.
Data moved
Choose how much data you want to move from PostgreSQL to PostgreSQL each month.
GB
Choose number of sources and destinations.
Why pay more?
Move the same data for a fraction of the cost.
What customers are saying
Estuary is our preferred CDC solution for importing data from application databases into BigQuery for analytics. It offers a transparent pricing structure, timely support responses, and an intuitive CLI tool for bulk configuration tasks. In contrast, other market solutions often have ambiguous pricing and fewer options for precise data replication across environments. This makes choosing to use Estuary an obvious decision.
Estuary allows us to integrate low-latency CDC and connect to SaaS apps across our entire reporting stack and it’s the only solution that we’ve found that lets us do both.
Getting started with Estuary
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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 PostgreSQL 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.
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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.
