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IBM watsonx.data as a Service - GenAI Ready Data Lakehouse for AWS

IBM Software

Reviews from AWS customer

3 AWS reviews

External reviews

166 reviews
from and

External reviews are not included in the AWS star rating for the product.

2-star reviews ( Show all reviews )

    Sunandan G.

Complex Setup and Rising Costs at Scale Despite a Strong Lakehouse Foundation

  • April 26, 2026
  • Review provided by G2

What do you like best about the product?
its open lakehouse architecture, which lets you query data across multiple sources without moving it.
It also delivers strong performance with built-in query optimization and integrates easily with existing data tools, making analytics faster and simpler.
What do you dislike about the product?
setup and configuration can feel complex, especially for smaller teams without strong data engineering support.
It can also become expensive at scale, particularly when handling large workloads or advanced features.
What problems is the product solving and how is that benefiting you?
solves the problem of scattered data by letting you access and query data across different storage systems without moving it into one place.
This benefits you by reducing data duplication, lowering costs, and enabling faster, more efficient analytics and decision-making.

    NamanJain

Faced a steep learning curve but have streamlined end-to-end machine learning workflows

  • December 02, 2025
  • Review from a verified AWS customer

What is our primary use case?

My main use case for IBM Watson Studio is the end-to-end ML life cycle.

A specific example of a project where I used IBM Watson Studio for the end-to-end machine learning life cycle is that I built a data pipeline that takes a Kafka stream and loads the data into our S3 bucket catalog. Then I built a data pipeline on top of it which parses the catalog and provides structured data for our in-house NER recognition model.

What is most valuable?

The best features IBM Watson Studio offers are that it is good for big and complex organizations, it is multi-cloud, it has an on-prem facility, and it also has strong visual tools.

The strong visual tools have helped my organization, which is currently cloud supported and has an on-prem server as well, as IBM Watson Studio serves as a use case for both of them.

IBM Watson Studio has positively impacted my organization by increasing work efficiency. I have noticed the work efficiency increase as it is an end-to-end ML pipeline in one place.

What needs improvement?

I think IBM Watson Studio can be improved.

I wish learning IBM Watson Studio could be easier and more gradual, as it is a complex task. Also, I think pricing is a bit high.

For how long have I used the solution?

I have been working in my current field for three plus years.

What do I think about the stability of the solution?

IBM Watson Studio is stable in my experience.

How are customer service and support?

I have not had any experience with customer support for IBM Watson Studio as I have not used it.

How would you rate customer service and support?

Which solution did I use previously and why did I switch?

We are still using Google AI Studio before IBM Watson Studio, and we have not particularly switched completely to IBM Watson Studio.

We are using Google AI Studio as another option, but I did not evaluate other options before choosing IBM Watson Studio.

What other advice do I have?

I would advise others looking into using IBM Watson Studio to just use the tutorials available to see all the features. I rate this product a 4.

Which deployment model are you using for this solution?

Hybrid Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)

    Online Media

They provide great support for a difficult product.

  • February 01, 2019
  • Review provided by G2

What do you like best about the product?
They offer support on Cassandra which is difficult to install and maintain.
What do you dislike about the product?
Their installer is command run instead of using traditional Unix packages.

They don't natively support Amazon Linux.
What problems is the product solving and how is that benefiting you?
Support Cassandra.

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