Fivetran vs. Stitch: In-Depth Comparison 2023

Vinesh Arun
September 5, 2023
min read


It’s no surprise that you’re wondering what the differences between Fivetran and Stitch are, because both ETL tools have very similar philosophies and approaches to the same problem: centralizing a company's data without  building or maintaining a single in-house data pipeline.

Fivetran Overview

Fivetran is a cloud-based ETL tool that targets data teams — specifically analytics engineers and data engineers. Fivetran’s thousands of customers use the product to automate data movement from SaaS tools to data stores like your warehouse for analytics use cases. It's considered a leader in the ETL space and continues to operate autonomously.

Stitch Data Overview

Candidly, at a high-level, Stitch Data is pretty similar. Stitch is a cloud-based ETL tool that targets developers. Stitch also has a large customer base that uses it to set up and forget data pipelines between SaaS applications and your database, data warehouse, or data lakes. In 2018, Stitch was acquired by Talend and is part of Talend Data Fabric.

Features Head to Head


Fivetran and Stitch both are in active development which is why the number of connectors for both continue to grow. Both ETL solutions also offer major data stores as destinations.


That being said, Fivetran has a fair amount more connectors offered, and it wouldn’t be surprising if this gap continues to widen given Fivetran’s autonomy and unicorn status vs. Stitch which was acquired years ago.

Custom connectors can be built with Fivetran’s cloud functions. You can code custom functions to edit connectors. And because Fivetran supports multiple serverless platforms like Azure functions, Google Cloud functions, and AWS Lambda, functions can be written using C#, F#, Go, Java, Node.js, or Python.


With Stitch you can use Singer to connect a new data source. It’s important to note that of the hundreds of Singer connectors Stitch can incorporate, only the popular connectors continue to be maintained by the community leaving the rest less reliable and of poorer quality.

If only one solution doesn’t offer the connector you need, no need to read the rest of the article — go with the product that does. Otherwise, consider additional factors below.

The winner on connectors is… Fivetran.



Fivetran does not transform data prior to loading, but instead does some common normalizations. It focuses more on support for post-load transformations with SQL and Fivetran works well with dbt too.


With Stitch, you’re able to use some of Talend’s toolset for pre-load transformations. MapReduce can also be used to transform data, which would be written in SQL, Java, and Python. You also can choose to push data into your warehouse and then process it once that’s done. However, Stitch only allows for transformations that are required for compatibility with the destination (e.g. de-nesting data, translating data types).

The winner on transformations is… it’s a tie (really depends on what you prefer, dbt, SQL, Python, you choose!)


Both offer security features that land them big customer logos. Both are SOC II, HIPAA, and GDPR compliant and offer SSL-based encryption.

The winner on security is… it’s a tie



Fivetran has customer support channels and ticketing systems in place with better SLAs on higher pricing tiers. Fivetran claims response times as fast as 1 hour for customers on the Standard plan and above, but replies are not necessarily solutions to your problem but just a response from an agent. Customers often have to submit a form and wait for a reply if not on enterprise where expedited support is available. Documentation is thorough and available, managed internally by Fivetran. People really do praise Fivetran for their support and their documentation.


Stitch provides in-app chat support to all customers, and phone support is available for Enterprise customers. Stitch, unlike Fivetran, provides open-source documentation, meaning anyone can request to make changes to the repository. This helps the documentation be more up to date because it's constantly being reviewed and suggestions for changes are made frequently.

Neither company offers any product training.

The winner on support is… Fivetran



Fivetran's pricing model charges based on monthly active rows, which can account for 2-18% of the total number of rows you have (according to their website). Raw number of rows are just the total number of records that are updated, deleted, or added. Monthly active rows means that even if the same row is updated 500 times, that row is only counted as 1 "active" row.

Fivetran also has a free tier as well as a 14 day free trial on paid plans.


Stitch has pricing that scales to fit a wide range of budgets and company sizes. Plans start at $100 billed monthly and goes up to $2500, though it certainly could be higher given that enterprises have to talk to sales and will negotiate pricing from there. The "2 months free" claim is if customers pay on an annual basis as opposed to monthly.

Stitch does not offer a free plan, but has a 14 day free trial on paid plans.

The winner on pricing is… it depends (if on the free plan, Fivetran. Otherwise Stitch tends to be cheaper)


When it comes to managed ETL-only data tools, Fivetran and Stitch are both market leaders and it’s clear that based on their popularity, you really could go either way. Despite the winner of each category either being a tie or leaning Fivetran, there’s a time and place for both depending on the company you’re at and the person implementing it.

If you’re part of the data team and want robust pipelines and great support at a premium price point, use Fivetran.

If you’re a developer and want a cheaper but solid option, use Stitch.

The best option for bidirectional ETL

For the best two-way ETL tool with predictable pricing and technical support, use Bracket.

Customers from mid-stage startups to enterprise companies use Bracket to keep your SaaS apps like Salesforce and data stores like Postgres in sync via two-way syncs. Similar to Heroku Connect but for any database.

Bracket removes the need for having two data syncing providers. Why does this matter? It's a way to get data collected from your web app into the hands of business teams, and a way to get customer-relevant data collected in tools like Salesforce into your web app for a personalized and reactive customer experience.

The two-way sync allows customers to have unified logging and error tracking, have up to real-time data refreshes, and don’t need to worry about data duplication or consistency problems

Interested in learning more about Bracket? Check out our docs here or go to our web app and get started!