# Some recommended data science software for e-commerce?

I’m looking at options for a few e-commerce teams who want to go beyond dashboards—recommendations, demand forecasting, and customer segmentation—without building an entire ML platform from scratch. I started with G2’s recommended data science software for e-commerce category to see what’s commonly used as the DS/ML core.

Here are a few I’m considering:

Dataiku: Collaborative platform for data prep, modeling, and delivery into business workflows. Useful when you need repeatable pipelines for segmentation, propensity, and forecasting.
Databricks: Data + AI platform for large-scale feature engineering and ML development. Often used when clickstream and transaction data volumes get big fast.
Snowflake: Cloud data platform commonly used as the centralized store for analytics and ML inputs. Helpful when teams want governed access to data across functions.
Amazon SageMaker: Managed ML for training and deploying models on AWS. Fits teams building recommendation or forecasting services close to AWS data systems.
DataRobot: Automated ML and model lifecycle tooling designed to speed up modeling cycles. Often used when teams want faster iteration and standardized deployment patterns.

For e-commerce use cases, what platform actually delivered the best results end-to-end (from data prep to model deployment), and where did you hit friction first?

##### Post Metadata - Posted at: 2 days ago - Net upvotes: 1 ## Related discussions - [How well does Trello scale into a larger team?](https://www.g2.com/discussions/1-how-well-does-trello-scale-into-a-larger-team) - Posted at: about 13 years ago - Comments: 6 - [Can we please add a new section](https://www.g2.com/discussions/2-can-we-please-add-a-new-section) - Posted at: about 13 years ago - Comments: 0 - [Quantifiable benefits from implementing your CRM](https://www.g2.com/discussions/quantifiable-benefits-from-implementing-your-crm) - Posted at: almost 13 years ago - Comments: 4