RedShift Agent for Gluesync: Target Integration

Amazon redshift logo screenshot

Core principles

This agent establishes a connection to Amazon RedShift via the RedShift JDBC driver, leveraging AWS S3 for high-performance bulk data loading. The agent uses CSV uploads to S3 followed by RedShift’s native COPY command for efficient snapshot and CDC batch ingestion.

Supported version

With this agent, you can target any Amazon RedShift deployment, including:

  • Amazon RedShift Serverless

  • Amazon RedShift provisioned clusters

  • Amazon RedShift Spectrum

Platform supported features

Feature Support Notes

Target role

✅

Writes to RedShift via the official JDBC driver with AWS S3 bulk load optimization.

Source role

❌

RedShift is supported as a target only.

Snapshots

✅

Snapshot batches are uploaded to S3 and loaded via RedShift COPY command for rapid ingestion.

CDC

❌

This agent does not currently support reading incremental changes from RedShift.

CDC type

N/A

This agent does not currently support reading incremental changes from RedShift.

Bulk load

✅

Supports staging-table bulk load workflows with AWS S3 CSV upload and COPY INTO.

Database pooling

✅

Supports connection pooling for efficient resource utilization across multiple pipelines.

Source persisted internal cache

N/A

Target-only connector.

Target persisted internal cache

N/A

Files are staged in AWS S3 during load jobs.

Driver / connector

RedShift JDBC driver + AWS S3

Bundled driver leverages S3 for high-throughput bulk writes.

Chains

N/A

Not supported being a target-only connector.

Truncate operation support (reading)

N/A

Target-only connector.

Truncate operation support (writing)

✅

Supports "TRUNCATE before snapshot" via RedShift SQL commands when enabled.

Bulk load via AWS S3

RedShift agent supports high-performance bulk loading through AWS S3 CSV uploads. This approach:

  • Batches CDC changes during mirroring cycles

  • Uploads data as CSV files to S3 staging buckets

  • Uses RedShift’s native COPY command for parallel ingestion

  • Provides optimal throughput for large datasets

For detailed information about bulk load workflows, see Bulk load.

Prerequisites

  • AWS account with RedShift cluster or Serverless workgroup

  • S3 bucket for staging bulk load files

  • IAM credentials with appropriate permissions (see Target setup)