G2

Gautam Ashish G.

Senior Data Analyst

Enterprise (> 1000 emp.)

10/6/2026

"Reliable, User-Friendly MongoDB-to-Snowflake Syncs That Save Engineering Time"

5/5

What do you like best about Fivetran?

What I like most about Fivetran is its reliability and ease of use, especially for ingesting MongoDB data into Snowflake. The data syncs consistently and accurately, and I have faced very few issues while using it.

The UI is intuitive and user-friendly, making it easy to set up connectors, monitor syncs, and troubleshoot when required. I also particularly like how Fivetran handles MongoDB's nested data and unnesting, which makes working with complex MongoDB structures much simpler.

Another major advantage is the ability to run transformations within Fivetran, allowing us to manage ingestion and transformation workflows in one platform.

From a Pricing / ROI perspective, I find the platform valuable because it significantly reduces the engineering effort required to build and maintain custom ingestion pipelines. The support and onboarding experience has also been helpful when setting up and working with connectors.

Finally, the increasing use of AI and intelligence features is a positive addition, as it helps make data engineering workflows more automated and efficient.

Overall, Fivetran provides a good combination of reliability, usability, automation, and reduced maintenance overhead, which is why it has been a strong choice for our data ingestion and transformation needs. Review collected by and hosted on G2.com.

What do you dislike about Fivetran?

There are not many major issues from my experience with Fivetran. One area that could be improved is the pricing, especially as data volumes and the number of connectors grow, since the overall cost can increase significantly over time.

For MongoDB, while the ingestion and unnesting capabilities work very well, some advanced configurations and transformation workflows could be made more intuitive and easier to manage directly through the UI. More intelligent recommendations around schema changes, transformation optimization, and monitoring would also make the platform even more useful.

That said, the reliability and the amount of engineering effort it saves largely offset these concerns in my experience. Review collected by and hosted on G2.com.

What problems is Fivetran solving and how is that benefiting you?

Fivetran significantly simplifies the process of ingesting and maintaining data pipelines, especially for our MongoDB-to-Snowflake use case. Instead of building and maintaining custom ingestion pipelines, we can configure a connector and let Fivetran handle the syncing, schema changes, and data movement reliably.

The MongoDB unnesting capabilities are particularly useful because they make complex and nested MongoDB data much easier to work with in Snowflake. The syncing has been very consistent in my experience, with minimal issues and very little manual intervention required.

The UI also makes it easy to configure connectors, monitor syncs, identify issues, and troubleshoot when needed. Fivetran's transformation capabilities further help us prepare and transform the data without having to build everything from scratch.

Overall, it reduces engineering and maintenance effort, improves reliability, and allows the team to focus more on analytics and business use cases rather than managing data pipelines. The time saved and reduced operational overhead provide good ROI for us. Review collected by and hosted on G2.com.