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REAL-TIME ETL & CDC

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Continously ingest and deliver both streaming and batch change data from 150+ of sources using Estuary's custom no-code connectors.

  • <100ms Data pipelines
  • 200+ Connectors
  • 2-5x less than batch ELT
01. Select a source02. Transform in-flight03. Deliver to PostgreSQL
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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.

For more details about the PostgreSQL connector, check out the documentation page.

How to connect your data source to PostgreSQL in 3 easy steps

1

Connect your data source

Select from more than 100 supported databases and SaaS platforms including PostgreSQL, MySQL, SQL Server, MongoDB, and Kafka.

2

Prepare and transform your data

Apply transformations and schema mapping as data moves whether you are streaming in real time or loading in batches.

3

Sync to PostgreSQL

Continuously or periodically deliver data into your destination with support for change data capture and reliable delivery for accurate insights.

Learn more with some related videos

Dive deeper into PostgreSQL with tutorials and walkthroughs from our YouTube channel.

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All data connections are fully encrypted in transit and at rest. Estuary also supports private cloud and BYOC deployments for maximum security and compliance.

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HIGH THROUGHPUT

Distributed event-driven architecture enable boundless scaling with exactly-once semantics.

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DURABLE REPLICATION

Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.

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REAL-TIME INGESTION

Capture and relay every insert, update, and delete in milliseconds.

Real-timehigh throughput

Point a connector and replicate changes to PostgreSQL in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 200+ of batch and real-time connectors to move and transform data using ELT and ETL.

  • Ensure your PostgreSQL insights always reflect the latest data by connecting your databases to PostgreSQL with change data capture.
  • Or connect critical SaaS apps to PostgreSQL with real-time data pipelines.

See how you can integrate any source with PostgreSQL:

Details

or choose from these popular data sources:

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PostgreSQL
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MySQL
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SQL Server
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MongoDB
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Apache Kafka
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BigQuery
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Snowflake Data Cloud

Don't see a connector?Request and our team will get back to you in 24 hours

Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.

Feature Comparison

EstuaryBatch ELT/ETLDIY PythonKafka
Price$$$-$$$$$-$$$$$-$$$$
Speed<100ms5min+Varies<100ms
EaseAnalysts can manageAnalysts can manageData EngineerSenior Data Engineer
Scale
Maintenance EffortLowMediumHighHigh
Detailed Comparison

Deliver real-time and batch data from DBs, SaaS, APIs, and more

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Popular sources/destinations you can sync your data with

Choose from more than 100 supported databases and SaaS applications. Click any source/destination below to open the integration guide and learn how to sync your data in real time or batches.