Amazon Redshift now scales data ingestion automatically with concurrency scaling for batch workloads

Amazon Redshift now extends concurrency scaling to support high-volume data ingestion workloads, enabling concurrency scaling for Amazon Redshift COPY queries from Amazon S3. This means your data pipelines no longer have to choose between ingestion speed and query performance—even during peak demand.

Organizations running time-sensitive data operations—real-time analytics, continuous ETL, or high-frequency reporting—often face ingestion bottlenecks during traffic spikes. Until now, concurrency scaling supported read queries, but write-heavy workloads could still experience resource contention with concurrent queries. With this launch, Amazon Redshift automatically provisions additional compute capacity to absorb burstiness in ingestion workloads, delivering:

• Faster COPY performance – For batch workloads, concurrency scaling now supports COPY for Parquet and ORC file formats from Amazon S3. Load multiple files concurrently without queuing delays, even under heavy concurrent workloads by enabling concurrency scaling for Amazon Redshift COPY queries.
• Zero operational overhead – No manual cluster resizing or workload scheduling required. Concurrency scaling is enabled and disabled automatically on Amazon Redshift Serverless based on the demand or based on a pre-set configurations in Amazon Redshift Provisioned.

This feature is generally available across all AWS commercial regions and AWS GovCloud (US) regions for both Amazon Redshift Serverless and provisioned data warehouses. No migration or configuration changes are required — enable concurrency scaling and your ingestion workloads will benefit immediately. To learn more, visit the Amazon Redshift concurrency scaling documentation.