Highly recommend Fivetran
December 02, 2021

Highly recommend Fivetran

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Fivetran

We use Fivetran as our Extract Transform Load provider bringing data from all our various third-party services into our Data Warehouse in Microsoft Azure. Personally, I've used it extensively with Twilio's sendgrid connector in bringing and formatting all of our email and notification data into the warehouse for data analysts internally to run more extensive analysis on it.
  • UI is very clean.
  • Documentation is easy to use.
  • Plenty of connectors for different third party services.
  • Honestly, not much they're already crushing it!
  • If I had to say one thing, I guess I would say make it more accessible to non-data engineers.
  • Security.
  • Reliability.
  • Speed.
  • I can't quantify it, but our entire data process runs on Fivetran.
  • It's invaluable.
We never seriously considered using anything else. Our data engineers had used Fivetran extensively in previous roles so when it came time to make a decision, there wasn't much of a process. They gladly signed the contract with Fivetran pretty quickly.

Do you think Fivetran delivers good value for the price?

Yes

Are you happy with Fivetran's feature set?

Yes

Did Fivetran live up to sales and marketing promises?

Yes

Did implementation of Fivetran go as expected?

Yes

Would you buy Fivetran again?

Yes

I think it's suited best for what it was built for, ETL pipelines expedited. If you are a startup that has a software product with various different data sources that you need to quickly and reliably bring all together to some kind of centralized data store, Givetrain is well suited for this use case. If that isn't part of your business needs to do this data consolidation before any analysis it probably isn't well suited for your use case.

Fivetran Feature Ratings

Connect to traditional data sources
7
Connecto to Big Data and NoSQL
6
Simple transformations
9
Complex transformations
8
Data model creation
8
Metadata management
8
Business rules and workflow
7
Collaboration
9
Testing and debugging
6
Integration with data quality tools
6
Integration with MDM tools
7