Vast selection of built-in connectors
August 08, 2025

Vast selection of built-in connectors

Sumit Mehta | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Software Version

Gathr Pro

Overall Satisfaction with gathr.ai

We use Gathr.ai primarily for data integration across a variety of source systems— internal databases, SaaS applications, marketing tools, etc. The goal is to bring all this data together in one place to power multiple downstream use cases. The platform’s comprehensive library of connectors has saved our engineers a lot of time and supported our pipeline development efforts.

Pros

  • Gathr.ai offers a vast collection of built-in connectors allowing us to pull data from diverse sources like Salesforce, HubSpot, and MySQL.
  • Its ability to ingest large volumes of data smoothly is commendable.
  • The drag-and-drop visual canvas helps build data integration pipelines effortlessly.

Cons

  • So far we’ve had a smooth experience with the tool and have gotten timely responses from the support team as well.
  • Our engineering team has saved substantial time and effort by using their built-in data connectors.
  • Business users now get access to clean, integrated data faster, improving time-to-insight for key use cases.
  • Runs concurrent workflows and delivers predictable price-performance.
The interface is intuitive, and the prebuilt connectors eliminate a lot of complexity.

Do you think gathr.ai delivers good value for the price?

Yes

Are you happy with gathr.ai's feature set?

Yes

Did gathr.ai live up to sales and marketing promises?

Yes

Did implementation of gathr.ai go as expected?

Yes

Would you buy gathr.ai again?

Yes

It works particularly well for ingesting both batch and real-time data. We've used it in scenarios where rapid integration was critical — and it held up well. It's also adept at handling a mix of structured and unstructured data.

gathr.ai Feature Ratings

9.0
Connect to traditional data sources
9
Connecto to Big Data and NoSQL
9
10.0
Simple transformations
10
Complex transformations
10
10.0
Data model creation
10
Metadata management
10
Business rules and workflow
10
Collaboration
10
Testing and debugging
10
10.0
Integration with data quality tools
10
Integration with MDM tools
10

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