Estuary

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Capture data from PostgreSQL Batch and deliver it to your destinations using Estuary's pre-built connectors. Build pipelines for real-time, incremental, or batch data movement based on connector capabilities.

  • <100ms to batch
  • 200+ connectors
  • Managed data pipelines
01. Move from PostgreSQL Batch02. Transform in-flight03. Select a destination
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PostgreSQL Batch connector details

The PostgreSQL Batch Query connector in Estuary captures data from PostgreSQL databases by periodically executing queries and loading the results into Estuary collections. It is useful when logical replication is unavailable, when capturing from database views or certain read replicas, or when you need custom SQL queries.

  • XMIN-based incremental capture for regular PostgreSQL tables using the xmin system column
  • Initial full backfill followed by incremental updates when XMIN mode is used
  • Cursor-based incremental capture using fields such as timestamps or incrementing IDs
  • Full-refresh capture for tables or views without a cursor
  • Custom SQL queries for filtering, aggregations, or capturing specific subsets of data
  • Configurable polling schedules, with a default interval of 5 minutes
  • Optional discovery of PostgreSQL views
  • Automatic use of primary keys as Estuary collection keys when available
  • Support for self-hosted PostgreSQL and managed platforms, including Amazon RDS and Aurora, Google Cloud SQL, and Azure Database for PostgreSQL

For ordinary tables, discovered bindings use XMIN mode by default. The first poll performs a full backfill, and subsequent polls capture rows with newer transaction IDs. Other bindings can use cursor-based incremental queries, full refreshes, or custom query templates.

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

How to connect PostgreSQL Batch to your destination in 3 easy steps

  1. 1

    Connect PostgreSQL Batch as your data source

    Securely connect PostgreSQL Batch and choose the objects, tables, or collections you need to sync.

  2. 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. 3

    Deliver to your destination

    Continuously or periodically deliver your data to the destination you choose, based on the capabilities and configuration of your pipeline.

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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.

HIGH THROUGHPUT

Distributed, event-driven architecture scales for demanding data workloads.

DURABLE COLLECTIONS

Store data as it moves so you can transform, replay, and deliver it downstream.

FLEXIBLE LATENCY

From <100ms CDC and real-time streaming to scheduled batch, depending on connector capabilities.

From <100ms to batch

Estuary supports CDC, real-time streaming, incremental syncs, and scheduled batch across its connector ecosystem. Capture data from PostgreSQL Batch using the cadence supported by the connector, then transform and deliver it to the destinations your team uses.

  • Connect PostgreSQL Batch to warehouses, databases, data lakes, search platforms, and event systems through Estuary-supported destinations.
  • Capture once and reuse PostgreSQL Batch data across transformations and multiple downstream destinations without rebuilding source extraction.

See where you can send PostgreSQL Batch data:

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or choose from these popular destinations:

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Feature Comparison

EstuaryBatch ELT/ETLDIY PythonKafka
Price$$$-$$$$$-$$$$$-$$$$
Latency<100ms to scheduled5min+Varies<100ms
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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.