G2

Kundan K.

Research Assistant

Enterprise (> 1000 emp.)

10/27/2026

"Seamless AWS Fit with Powerful, Predictable Analytics at Scale"

4.5/5

What do you like best about Amazon Redshift?

Amazon Redshift’s biggest advantage is how naturally it fits into the wider AWS ecosystem, especially S3, IAM, and AWS Glue. Its Massively Parallel Processing (MPP) architecture tackles complex multi-table joins across massive datasets—10M+ records—with little friction, which matters when teams need fast, exploratory analysis and fraud modeling.

Redshift Spectrum adds another layer of usefulness. It lets us query cold or unstructured data straight from our S3 data lake with standard SQL, avoiding the overhead and cost of loading everything into the warehouse first. Since it’s based on familiar PostgreSQL syntax, analysts and engineers can ramp up quickly. Redshift also provides a highly predictable pricing and performance model, making enterprise cloud compute costs easier to manage at scale than with many other modern data warehouses. Review collected by and hosted on G2.com.

What do you dislike about Amazon Redshift?

Scaling compute isn't as instant as I'd like. The separation of compute and storage still feels less flexible compared to Snowflake. Concurrency can also be a real headache. When too many analysts hit the cluster with heavy queries at once, things queue up and slow down. It also requires a bit too much manual maintenance under the hood. You still have to stay on top of vacuuming and analyzing tables to keep query performance sharp. Review collected by and hosted on G2.com.

What problems is Amazon Redshift solving and how is that benefiting you?

It solves the problem of querying massive, fragmented datasets at scale. In fraud analytics, we deal with tens of millions of rows of payment logs, user telemetry, and third-party vendor data. Redshift centralizes all of this and lets me run complex SQL joins across our structured tables and our S3 data lake without queries timing out.

The biggest benefit to me is speed to insight. I can pull 10M+ records, run heavy anomaly detection queries, and identify emerging fraud patterns in minutes instead of waiting hours for data engineers to move things around. It keeps me focused on actual analysis rather than pipeline management. Review collected by and hosted on G2.com.