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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
Neon PostgreSQL connector details
Estuary’s Neon PostgreSQL connector enables real-time change data capture (CDC) from your Neon-hosted PostgreSQL databases. It uses Neon’s logical replication feature and Estuary’s streaming engine to continuously capture inserts, updates, and deletes into Flow collections for downstream analytics and operational use cases.
- Streams real-time changes from Neon PostgreSQL using logical replication
- Automatically configures replication slots, publications, and watermarks for reliable CDC
- Supports initial backfills and incremental syncs, with the flexibility to skip backfills for large datasets
- Ideal for building cloud-native, low-latency pipelines for analytics and applications
- Secure by design: Supports Estuary’s Private Deployment and BYOC options, giving teams full control over data residency, compliance, and network security
💡 Tip: If you’re capturing from self-managed or non-Neon PostgreSQL instances, explore the standard Estuary PostgreSQL CDC connector for similar real-time capabilities.
HIGH THROUGHPUT
Distributed event-driven architecture enable boundless scaling with exactly-once semantics.
DURABLE REPLICATION
Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.
REAL-TIME INGESTION
Capture and relay every insert, update, and delete in milliseconds.
Real-timehigh throughput
Point a connector and replicate changes from Neon 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 Neon PostgreSQL insights always reflect the latest data by connecting your databases to Neon PostgreSQL with change data capture.
- Or connect critical SaaS apps to Neon PostgreSQL with real-time data pipelines.
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Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
| Estuary | Batch ELT/ETL | DIY Python | KAFKA | |
|---|---|---|---|---|
| Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
| Speed | <100ms | 5min+ | Varies | <100ms |
| Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
| Scale |
Deliver real-time and batch data from DBs, SaaS, APIs, and more
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