Stream data from Oracle Database (Batch) to Google Cloud SQL for PostgreSQL
Move data from Oracle Database (Batch) to Google Cloud SQL for PostgreSQL in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.
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- 200+Connectors
- 5500+Active users
- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate Oracle Database (Batch) with Google Cloud SQL for PostgreSQL in 3 simple steps
- 1
Connect Oracle Database (Batch) as your data source
Set up a source connector for Oracle Database (Batch) in minutes. Estuary supports streaming (including CDC where available) and batch data capture through events, incremental syncs, or snapshots — without custom pipelines, agents, or manual configuration.
- 2
Configure Google Cloud SQL for PostgreSQL as your destination connector
Estuary supports intelligent schema handling, with schema inference and evolution tools that help align source and destination structures over time. It supports both batch and streaming data movement, reliably delivering data to Google Cloud SQL for PostgreSQL.
- 3
Deploy and Monitor Your End-to-End Data Pipeline
Launch your pipeline and monitor it from a single UI. Estuary guarantees exactly-once delivery, handles backfills and replays, and scales with your data — without engineering overhead.

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_ROWSCNto 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.

Google Cloud SQL for PostgreSQL connector details
The Google Cloud SQL for PostgreSQL materialization connector in Estuary delivers data from Estuary collections into PostgreSQL tables hosted on Google Cloud SQL. It supports continuous materialization from real-time or batch pipelines, using standard merge-based updates by default with optional delta updates for applicable workloads.
- Standard merge-based updates by default to keep destination rows synchronized
- Optional delta updates for workloads where changes should be applied incrementally
- Optional hard deletes so records deleted upstream can also be removed from destination tables
- Automatic table creation for configured materialization bindings
- Configurable PostgreSQL schemas and table names for individual bindings
- Google Cloud IAM or username/password authentication
- Direct Google Cloud SQL connectivity or SSH tunneling for private network configurations
- Configurable SSL connection behavior
- Custom SQL during table creation for indexes or other table-level configuration
- Automatic quoting of PostgreSQL reserved words when used as field names
Estuary creates the destination tables used by the materialization; manually pre-created tables are not supported. The default PostgreSQL schema is public, but you can configure another default schema or override it for individual bindings.
Estuary in action
See how to build end-to-end pipelines using no-code connectors in minutes. Estuary does the rest.
Spend 2-5x less
Estuary customers not only do 4x more. They also spend 2-5x less on ETL and ELT. Estuary's unique ability to mix and match streaming and batch loading has also helped customers save as much as 40% on data warehouse compute costs.

Oracle Database (Batch) to Google Cloud SQL for PostgreSQL pricing estimate
Estimated monthly cost to move 800 GB from Oracle Database (Batch) to Google Cloud SQL for PostgreSQL is approximately $1,000.
Data moved
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Frequently Asked Questions
Is this integration suitable for production workloads?
Yes. Estuary pipelines are designed for production use, with exactly-once delivery semantics, automated backfills, and continuous operation at scale.
Can I control where my data runs and is processed?
Yes. Estuary offers multiple deployment options, including fully managed SaaS, private deployments, and bring-your-own-cloud (BYOC). This allows teams to control where their data plane runs and meet security, compliance, and networking requirements. Learn more about Estuary's security and deployment options.
Can I build this Oracle Database (Batch) to Google Cloud SQL for PostgreSQL integration manually?
Yes, it's possible to build a manual pipeline using custom scripts, scheduled jobs, or open-source tools. However, manual approaches typically require ongoing maintenance, custom error handling, schema management, and operational overhead. Estuary simplifies this by providing a managed pipeline with built-in reliability, scaling, and monitoring.
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