The future of data integration: what iPaaS & Workflow Automation tools got wrong

Define the data you want in your preferred style: You can expose a whole table with our table selector, use our visual audience builder to define your data in our point-and-click UI, define your data in SQL or with an existing dbt model.

Next, choose your end destination tool (ex: Salesforce) and map the fields in your data to fields in your destination tool that you want to update.

Lastly, schedule how frequently you want your data to sync by scheduling it on a set interval (ex: every minute or hour), via API call or doing it manually yourself.

The beauty of this declarative approach is that everything else is handled for you. With iPaaS, you need to worry about painfully common "edge cases" like foreign keys, API limits, and more that lead to a nasty tree of if/else statements

Why is this method better?

Declarative data integration is superior to imperative data integration for many reasons, the main of which being that it addresses all the edge cases so you don’t have to. For instance, conventional iPaaS tools only allow you to match rows based on specific ID’s (ex: SalesforceID or HubspotID). With Hightouch, you can match rows by matching fields of your choosing. Likewise, iPaaS solutions send all your data each time, pulling more data than is needed and potentially adding to your bill if your destination tool is charging per API call. Hightouch is able to diff the results between your syncs, enabling you to only send the rows that changed. This saves you a huge amount of time and money. In addition, iPaaS solutions often run into API rate limits. With Hightouch, if any of your rows get rate limited, they will automatically be retried later so that your entire sync does not fail. Hightouch also stores logs in our live debugger, so that you can quickly identify and fix errors. All of this is done for you, without you even having to think about it. You just have to choose which data source and which destination you want to sync your data to.

Data integration is a problem that is not going away anytime soon. In fact, it will most likely become more challenging as the data ecosystem expands, but since companies can choose from the “best of breed” solutions, the products will continue to improve for everyone. At the end of the day, every business is different and every employee has a specific role they were hired for. The question you have to ask, is what could be enabled if data integration was not a blocker for your various teams?