Move your data from Oracle Database (Batch) with your free account

Capture data from Oracle Database (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
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01. Move from Oracle Database (Batch)02. Transform in-flight03. Select a destination

Oracle Database (Batch) connector details

The Oracle Database Batch Query connector in Estuary captures data by periodically querying Oracle tables and views and loading the results into Estuary collections. It supports several query patterns, making it useful when LogMiner-based CDC is unavailable, when capturing from database views or read replicas, or when you need custom SQL queries.

ROWSCN-based incremental capture using Oracle’s ORA_ROWSCN to identify rows modified since the previous poll
Cursor-based incremental capture using fields such as update timestamps, creation timestamps, or incrementing IDs
Full-refresh capture for tables or views without a suitable cursor
Custom SQL queries for filtering, aggregations, or capturing specific subsets of data
Configurable polling schedules, with a default interval of 5 minutes
Automatic table discovery across accessible Oracle schemas
Primary-key-aware collections, using discovered primary keys when available
Support for Oracle Database 11g and later, including self-hosted databases, Amazon RDS, Oracle Cloud Infrastructure, and other managed platforms

For discovered tables, the connector can use ORA_ROWSCN to perform an initial full backfill and then capture only new or updated rows on subsequent polls. When no cursor is configured, the full table or view is re-read during each polling cycle.

For more details about the Oracle Database (Batch) connector, check out the documentation page.

How to connect Oracle Database (Batch) to your destination in 3 easy steps

1
Connect Oracle Database (Batch) as your data source
Securely connect Oracle Database (Batch) and choose the objects, tables, or collections you need to sync.
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
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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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 Oracle Database (Batch) using the cadence supported by the connector, then transform and deliver it to the destinations your team uses.

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

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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	$	$$-$$$$	$-$$$$	$-$$$$
Latency	<100ms to scheduled	5min+	Varies	<100ms
Ease	Analysts can manage	Analysts can manage	Data Engineer	Senior Data Engineer
Scale
Maintenance Effort	Low	Medium	High	High