A Candid Look at Fivetran, Including Pros and Cons

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Bradley Nielsen

Senior Tech Specialist
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Bradley is a well-rounded developer in the field of data science and analytics. He has been a developer and architect on a wide range of data initiatives in multiple industries. Bradley's primary specialty is in data engineering: developing, deploying, and supporting data pipelines for big data and data science. He is proficient in Python, C#, SQL Server, Apache Spark, Snowflake, Docker, and Azure.
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Since Marlabs recently became a Fivetran partner, we thought we’d ask data engineer Bradley Nielsen to give you an assessment of the service. Nielsen has deep experience with Fivetran and helping our clients use the product.

Note that being a partner means Fivetran has vetted Marlabs as a company with the expertise to help organizations use their service effectively and efficiently. Nielsen’s thoughts are below.

Who or What Is Fivetran?

Fivetran is a data infrastructure company that helps organizations move, transform, and activate data across the enterprise.

Its platform connects data from source systems (ERPs, CRMs, SaaS applications, databases, and files) to destinations, such as data warehouses and data lakes.

In June 2026, Fivetran completed a merger with dbt Labs, bringing together Fivetran's data movement capabilities with dbt's data transformation capabilities. Initially operating as Fivetran + dbt Labs, the combined company is building an open data infrastructure foundation for analytics and AI.

Fivetran is no longer solely focused on data movement. Merging with dbt expands its capabilities across data movement, transformation, and the infrastructure needed to support analytics and AI.

Simply put, Fivetran moves data from where it's generated (source systems) to where organizations can analyze and use it.

For example, it can continuously move data from a company's CRM into a data warehouse, such as Snowflake or Google BigQuery, where it can be transformed and prepared for analytics and AI.  

Fivetran’s mission is to “make access to data as simple and reliable as electricity.”

What Are Fivetran's Strengths?

Fivetran has a 4.5-star rating on Gartner Peer Insights (Oct. 2025), based on more than 300 reviews and was named a Challenger in the 2025 Gartner Magic Quadrant for Data Integration Tools, a status it has held for six years.

Fivetran's strengths include its strong execution, reliability, ease of use, and a broad connector ecosystem.

Simplicity and ease of use are also among Fivetran's strengths, reflected in its automated, fully managed approach to data movement.

Fivetran’s value proposition is that it can reduce the cost and engineering effort required to build and maintain data pipelines by:

  • Developing and maintaining connectors for you. To pull data from a source system often requires some form of custom integration code, commonly implemented through a connector. Connector complexity can range from relatively simple to highly advanced, depending on the source. Developing and maintaining these connectors requires time, money, and talent. Fivetran offers more than 700 prebuilt connectors and is constantly adding new ones.
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  • Pipeline management. Fivetran automates many pipeline management tasks, such as routing, error recovery, incremental loading, scheduling, schema change handling, and updates. This reduces the amount of pipeline maintenance required from your data engineers.
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  • Infrastructure management. Fivetran is fully managed SaaS platform, so there is no software to install and maintain, nor servers to manage. Fivetran manages the infrastructure required to run the pipelines.

Fivetran's merger with dbt Labs  brings data transformation capabilities into the combined company's broader infrastructure platform. Fivetran also offers capabilities related to data quality, governance, and observability.

How Much Does Fivetran Cost?

Fivetran’s costs are usage-based, depending primarily on the number of rows inserted, updated, or deleted and synced during a month -- called Monthly Active Rows (MAR).

The number of rows in a database isn't necessarily the number of MAR. Fivetran's model is based on rows that are actually inserted, updated, or deleted, not the total number of rows sitting in the source.

The important things to remember are that Fivetran:

  • Doesn’t charge extra when the same row is updated multiple times. If you load a row and then update it 10 times (within a month), you are charged for it only once.
  • Offers volume-based discounts as usage increases. The cost per MAR decreases as usage increases.
  • Doesn’t charge for initial historical syncs or qualifying resyncs. Once the initial sync is complete, new and changed data can count toward paid MAR.

Key Considerations

For some organizations with appropriate in-house talent, it may be more cost effective to develop your own pipelines. This is especially true for simple, high-volume pipelines like database-to-database integrations.

Estimating monthly active rows can be tricky, which can make Fivetran costs challenging to forecast.

Connecting to on-premises resources requires can require additional network configuration, such as an SSH tunnel, which is not trivial. Even with 700+ connectors, it does not support every possible data source.

Fivetran's Connector SDK allows organizations to build custom connectors for sources that aren't natively supported. Building and maintaining a custom connector still requires technical expertise and effort, which can reduce some of the platform's time-saving benefits.

Conclusion

At Marlabs, we pride ourselves on being technology agnostic. This means we recommend solutions based on what best meets an organization's needs, not just who our “favorite” is.

We are a Fivetran partner because we found this to be a great tool and strong solution for specific data integration needs.  

Depending on the situation, Fivetran is a great way to get up and running with a variety of connected sources of data quickly. This can significantly reduce time-to-value and  help move an organization’s data strategy forward by deliveringresults.

However, there are potential long-term cost considerations, especially as data volumes and pipeline activity grow.

Based on this evaluation, we would recommend Fivetran in situations where many data sources need to be connected quickly, and the total volume of data over a long period of time would make it cost justifiable.

Fivetran could also be a good temporary solution to prove results (the value of a data integration strategy) and help build a business case for building your own custom pipelines later down the road.