AWS First Steps
New feature

Amazon Redshift now supports concurrency scaling for streaming ingestion workloads from Amazon Kinesis data streams

Amazon Redshift introduces concurrency scaling for refreshes of streaming materialized views connected to Amazon Kinesis Data Streams, allowing main clusters or workgroups to be freed for higher-priority tasks

Starting with patch P203, Amazon Redshift supports concurrency scaling for refreshes of streaming materialized views connected to Amazon Kinesis Data Streams. This enables low-latency, high-speed data ingestion from KDS to Redshift data warehouses, reducing data access time and storage costs. Users can configure streaming ingestion using SQL commands, with each refresh capable of ingesting hundreds of megabytes per second. With concurrency scaling enabled, streaming workloads automatically scale, freeing the main Redshift cluster or workgroup to run other higher-priority workloads. This capability is immediately available in all AWS regions where Amazon Redshift is offered, helping build resilient analytics applications with predictable service level agreements.

Why it matters

This update affects users of Amazon Redshift's streaming ingestion feature, particularly those handling large data streams for analytical workloads. Concurrency scaling improves resource utilization and performance.

Read the original AWS announcement

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