Make vs. Fivetran

Integromat is the best tool for business automation in my opinion because unlike Zapier it allows us to integrate with any API even if the app is not available which allows us to create automation even with the less known apps that we use or the ones that we built internally for our own company.

Incentivized

Fivetran's business model justifies the use-case where we require data from a single source basically a lot of data but if the requirement is not on the heavier side, Fivetran comes to costly operation when compared to its peers. Otherwise, I'll recommend Fivetran for stability and update and seamless service provider.

Incentivized

• UI/UX Simplicity and Features
• Workflows are explained in details and even people without IT background can use the tool.
• Consumption is nicely tracked.
• Myriad of existing templates, solutions, and readymade connectors.

• Easily connects to source data using delivered connectors
• Transforms data into standard models and schemas
• Has very good documentation to help quickly setup connectors

Incentivized

• There are always new platforms and connections that we'd like to see
• More flexibility in paying for operations (tasks) on a sliding scale, instead of by tier
• More thorough support documentation on connecting various platforms and troubleshooting errors

Incentivized

• Very difficult to get connectors enhanced if a specific needed object is not supported by them
• Depending on the edition needed and the data volumes, can get quite expensive

Incentivized

At this point, it is firmly embedded in the DNA of the business and to give up the ability to automate workflows and create integrations on the fly would be a terrible idea.

Make's easy to understand user interface helps you to visualize what's happening at all times. Could use some tweaks around the navigation from a scenario specifically in the folders and back navigations. I can't tell you the amount of time wasted in that area. When you branch, you can't bring a branch back together in the same scenario which is kind of a bummer as well.

Incentivized

Very easy and intuitive to setup and maintain as there usually are not that many options. Very well documented (e.g. how to setup each connector, how the schema looks like, any specific features of this connector etc.). Also the operation is intuitive, e.g. you have status pages, log pages, configuration pages etc. for each connector.

Incentivized

It runs pretty well and gets our data from point A to point cluster quickly enough. Honestly, it's not something I think about unless it breaks and that's pretty rare.

Incentivized

The pricing schema is very attractive, almost 50% lower than the competition. You could start from free and then grow. It has a pretty big library of connections to other apps and services, which really helps you when everything is a mess. Integromat has a really easy-to-use interface. You could do almost everything with fewer than 5 clicks. Scenarios (automation steps to complete a routine) have graphics so you can configure them more easily.

Incentivized

Integromat allows us to do everything we used to do on Zapier but it doesn't limit us to only the popular apps, with Integromat we're integrating custom APIs and we get data from different servers through GET requests and it's exactly what we needed and Zapier couldn't provide it.

Incentivized

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.

Incentivized

• We used too many credits multiple times and had to buy them additionally, there are no prevention systems to setup to alert before it happens.
• Some consumption is difficult to understand and requires time and digging.
• It requires heavy internal effort to simplify things in Make in order for it to operate cheaper.
• Initial IT setup is paramount and determines a lot.

• It has been very positive in serving BI team with new source requests
• It has been OK at scaling to match as data volumes as source data size grows

Incentivized