Sync data from
Amazon Redshift to HubSpot

You have a few options on how to unblock your marketing and business teams using Hubspot. We've outlined the 5 most common options you can take to sync data between Redshift and Hubspot below:

Option 1: Reverse ETL (Hightouch)

Reverse ETL tools like Hightouch can run on top of the data warehouse enabling you to sync data directly from Redshift to Hubspot in real-time. With Hightouch all you have to do is define your data using SQL or your own existing data models and map them to the appropriate columns in your end destination.

Better yet, Hightouch doesn’t store any of your data which means it only exists within your own cloud environment. In addition to this, Hightouch also offers a visual audience builder for business users who don't know SQL. You can start syncing data today in six simple steps.

Step 1: Connect to Your Data Source

Step 2: Connect Hightouch to Your Destination

Step 3: Create a data model or leverage an existing one

You can use SQL to define your data directly in the Hightouch UI or even leverage your existing data models.

Step 4: Choose Your Primary Key

With Hightouch you can map on any unique key, not just users and accounts.

Step 5: Create Your Sync

Once you have created your sync, you simply have to choose the appropriate columns and map them to the fields in your end destination.

Step 6: Schedule Your Sync

Once your sync is created you can run it manually, define a set interval, or schedule it to run after a dbt job is completed.

The first integration with Hightouch is completely free so you can actually get started today. If you want to learn more about Reverse ETL, download our guide.

Option 2: Manual CSV Files

The most common and well-known way to move data from Redshift to Hubspot is through the usage of manual CSV files. This method involves you downloading a specific data set from Redshift and then uploading it directly to Hubspot. Doing this creates a few challenges though. Firstly, data stored in a CSV file becomes stale really quickly which makes it difficult for your sales and marketing teams to trust it.

This is not the most efficient way of moving data either because it's not a one-off request. Additionally, it's a manual process that requires you to download a CSV file every time your sales or marketing teams make a request. In addition to this, you have to ensure that all of the columns in your file match up with the columns that exist in Hubspot otherwise you risk ruining the data that lives in Hubspot (there is no undo button if you mess up an import).

Option 3: Custom Integrations

Building an in-house data pipeline to move data from Redshift to Hubspot could alleviate much of the manual effort involved in generating CSVs but this method also presents several challenges. Firstly, the APIs for Redshift and Hubspot are constantly changing, meaning that you have to be on the lookout for upstream or downstream changes to ensure your data pipeline is running smoothly.

Building a data pipeline is not an easy task. It’s resource-intensive and it pulls your engineering team away from the jobs that they were actually hired for. A custom data pipeline could work for you if you have relatively low amounts of data that you need to move, but if you need a custom integration for all of your additional SaaS applications and marketing tools it becomes nearly impossible to maintain.

Option 4: iPaaS (Integration Platform as a Service)

Workflow automation tools like Tray and Workato, are great options to move data from point “A” to “B”. As point-to-point solutions, that’s really all they can do. They exist to automate repetitive tasks and processes to improve efficiency.

These solutions can be a great option for simple use cases, but as soon as you go beyond that, you will find yourself writing custom code and soon be neck-deep in multiple if/then branches with numerous dependencies in each individual step. If the employee who created these workflows ever leaves, you will be stuck trying to piece together the mess he/she left behind.

Option 5: CDPs (Customer Data Platform)

CDPs fulfill a wide range of use cases and can be a great option for moving your data from Redshift to Salesforce. With a CDP you can easily consolidate all of your customer data into a centralized platform and then push it out to numerous SaaS applications and operational systems.

The problem with CDPs is that they created another source of truth in addition to your data warehouse. On top of this, CDPs can take over a year to implement, making it very difficult to get any value out of the solution. Even worse, CDPs own your data because it is no longer stored within your own cloud environment, so you might run into compliance issues.