AWS has released new Graviton-powered RG instances for its Amazon Redshift data warehouse service aimed at helping enterprises reduce both rising analytics costs and the operational complexity of modern lakehouse architectures.
At the core of the new instances is an integrated data lake query engine that AWS says can run SQL analytics across both Redshift warehouse data and Amazon S3 data lakes, delivering faster query performance and lowering analytics costs.
“Earlier, Amazon Redshift RA3 systems operated as two separate engines, with Redshift handling warehouse data and Spectrum handling S3 data lake queries. When a query required both, AWS had to coordinate between the two systems, which added complexity, slowed performance, and made Spectrum scan costs unpredictable,” said Pareekh Jain, principal analyst at Pareekh Consulting.
“The new RG instances combine those worlds into one integrated engine running directly inside Redshift itself. That means Iceberg, Parquet, and S3 lake data can now be queried natively alongside warehouse data with less movement, lower overhead, and better performance optimization while also eliminating separate Spectrum per-scan charges,” Jain added.
The separate Spectrum charges, the analyst further added, were increasingly becoming a pain point for enterprises as AI workloads drove higher query volumes, more machine-generated analytics, and greater data-processing demands, with many customers disliking Spectrum’s separate scan-based pricing because of the possibility of sudden bill spikes.
