Mage AI vs. Stitch, a Qlik product

Mage is well-suited for probability score for uptake of every product is calculated for customers using ML/ Regression models, choosing customers for a product/ Top products for a customer, based on the requirement and Identifying popular product combinations using association rules from Market Basket Analysis (or affinity Analysis)\Bundle these products as combos.

Incentivized

Stitch is very cheap and useful for small to medium size companies to ingest data from common apis/platforms in a quick and cheap way.

Incentivized

• Ranking algorithms.
• Cloud-based tool.
• Increase user engagement.

Incentivized

• Easy integration with many sources
• Extensible
• Not as expensive as fivetran

Incentivized

• Acquisition Contribution.
• Business Intelligence Reporting.
• Data Destinations.

Incentivized

• Stitch is not good at replicating document stores like MongoDB to relational databases. To be fair, this is a difficult task. Stitch flattens the objects, but the result is unwieldy.
• Stitch cannot replicate the same source to multiple sinks, which is inconvenient if you want to replicate some of a datastore's tables to Redshift and others to Redshift Spectrum, for instance.

Incentivized

Mage was the easiest in terms of ease of implementation due to its no-code functionality. However, Mage doesn't have a whole ecosystem like AWS and slightly falls behind there.

Incentivized

Stitch from Talend is way more cost effective and has a business model that better aligns with our company. From what I can tell Stitch from Talend has a better customer support platform as well and has been very easy to work with when issues have come up. They also seem less pushy when it comes to sales.

Incentivized

• Business Understanding.
• Data Acquisition and Understanding.
• Data Modeling and Evaluation.

Incentivized

• Good ROI in terms of being able to monitor cost performance from Google, Facebook, etc.
• Easy to have Salesforce data and Intercom data for dashboards.

Incentivized