AWS whips out Graviton-powered Redshift instances, claims 7x speed for data warehouse

Summary

Databases AWS whips out Graviton-powered Redshift instances, claims 7x speed for data warehouse AI agents asking questions in natural language apparently issue a lot more queries than your average SQL jockey AWS says it has boosted Redshift performance by bringing the data warehouse to its Graviton-powered instances, positioning it to handle AI agent workloads and fend off rivals in the analytics market.Redshift's new RG instances, powered by AWS Graviton processors, accelerate new query workloads by up to seven times. AWS claims the instances are up to 2.2x faster than the RA3 family, which it introduced in 2019, at 30 percent lower cost per vCPU. The updated query engine also lets users run SQL analytics across data warehouses and data lakes from a single engine, delivering up to 2.4x the performance of RA3 for Apache Iceberg and up to 1.5x for Apache Parquet. Amazon Redshift RG instances are available in AWS Regions including US East, US West, Asia Pacific, Canada (Central), Europe (Frankfurt, Ireland, Milan, London, Paris, Spain, Stockholm), and South America (São Paulo). AWS plans to publish a roadmap for future availability. Users can choose hourly billing with no commitments or Reserved Instances for cost savings. AWS recommends using its Pricing Calculator with your specific workload patterns to estimate bills. The combination of speed, cost efficiency, and an integrated data lake query engine mean Redshift RG instances could help the system cope with changing workloads from AI agents, which allow users to query data in natural language, AWS claims.Andrew Warfield, AWS VP and Distinguished Engineer, said Redshift engineers had worked closely with the Graviton team for a few years, and the announcement was the first of an expected string of integrations.He told The Register the performance improvement would help the data lakehouse system cope with the increasing demands of agent-driven workloads, as general business users query organizational data in natural ...