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REAL-TIME ETL & CDC

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Continously ingest and deliver both streaming and batch change data from 100s of sources using Estuary's custom no-code connectors.

  • <100ms Data pipelines
  • 100+ Connectors
  • 2-5x less than batch ELT
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01. Move from PostgreSQL02. Transform in-flight03. Select a destination
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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 Flow 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

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

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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 from PostgreSQL in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 100s 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.
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Feature Comparison

EstuaryBatch ELT/ETLDIY PythonKAFKA
Price$$$-$$$$$-$$$$$-$$$$
Speed<100ms5min+Varies<100ms
EaseAnalysts can manageAnalysts can manageData EngineerSenior Data Engineer
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