Heroku is a cloud platform as a service (PaaS) for efficiently building, deploying, monitoring, and scaling applications. Originally created to work with the Ruby programming language, Heroku is now part of the Salesforce platform and supports languages such as Java, Node.js, PHP, Python, and Scala. 

While Heroku makes it easy to develop production-ready applications fast, one question remains: how can you integrate your Heroku app data with the rest of your data infrastructure and workflows? ETL (extract, transform, load) is the de facto standard for enterprise data integration, moving information from one or more data sources into a target data warehouse (e.g. Amazon Redshift or Snowflake).

In this article, we'll discuss how you can use Heroku and ETL to get better analytics and reporting so you can make smarter data-driven decisions.

Table of Contents

  1. Heroku ETL Tip #1: Heroku Postgres
  2. Heroku ETL Tip #2: Heroku Redis
  3. Heroku ETL Tip #3: Heroku Connect
  4. Heroku ETL Tip #4: Heroku Add-ons
  5. Heroku ETL Tip #5: Data Analytics Platforms
  6. How Can Help with Heroku and ETL

Heroku ETL Tip #1: Heroku Postgres

Heroku Postgres is a fully managed "Postgres database as a service" offering from Heroku. It comprises an open-source SQL database running PostgreSQL, one of the most popular relational database management systems (along with other SQL databases such as MySQL, Microsoft SQL Server, IBM, and Oracle).

Because Heroku Postgres is by far the most used method of cloud data storage in Heroku, it's very much to your advantage to adopt it if at all possible. This is because your choice of ETL tool is more likely to have a data connector with Heroku Postgres, giving you an easy, pre-built way to extract data from your Heroku database.

Heroku ETL Tip #2: Heroku Redis

Don't want to use a SQL database for cloud storage of your Heroku data? NoSQL databases such as MongoDB are ideal for unstructured and "schema-less" data sets. With Heroku Redis, the Heroku platform offers a NoSQL alternative to Heroku Postgres.

Redis is a highly popular open-source, in-memory data structure store that you can use to implement NoSQLkey-value databases and application caches. Heroku Redis is Heroku's version of Redis, with all the project's traditional advantages, such as high availability and scalability. Like Heroku Postgres, the use of Heroku Redis makes it more likely you can find an ETL tool with a pre-built connector so that your data flows directly into your choice of data warehouse.

Heroku ETL Tip #3: Heroku Connect

Heroku Connect is a data integration service that enables real-time synchronization between your Heroku Postgres database and your Salesforce data. With Heroku Connect, you can set up a one- or two-way connection for instantaneous data replication. Any changes that you make to the underlying Salesforce database replicate the connected Heroku Postgres database (and vice versa if you've enabled two-way synchronization).

By using Heroku Connect's user-friendly, point-and-click interface, you can separate your Salesforce REST API interactions from the underlying logic of your Heroku applications. Heroku Connect makes it easier for you to maintain data integrity and data quality as your data infrastructure scales and grows more complex.

Heroku ETL Tip #4: Heroku Add-ons

​Heroku Connect is actually just one example of Heroku add-ons, which are plug-in components, tools, and services for extending the functionality of your Heroku applications. Some other popular Heroku add-ons include:

  • Bucketeer for accessing Amazon S3 (Simple Storage Service)
  • SFTP To Go for managed SFTP/FTPS cloud storage as a service
  • RuntimeError for tracking and managing runtime errors using GitHub

Of course, Heroku also comes with the add-on for ETL and ELT data integration. can both send data to and receive data from Heroku Postgres. seamlessly connects with tools, services, and data stores in AWS, Microsoft Azure, and Google Cloud. In the Google cloud alone, users can integrate with Google Analytics, Google Sheets, Google BigQuery data warehousing, and more.

Heroku ETL Tip #5: Data Analytics Platforms

Last but not least, doing Heroku ETL right means choosing the right reporting and analytics platforms as the destination for your Heroku app data. Tableau, Microsoft Power BI, Looker, and Amazon QuickSight are just a few of the possible business intelligence and analytics tools at your fingertips—but first, make sure there's a technically feasible way to get your Heroku data from source to destination.

Of course, data analytics isn't the only potential use case for your Heroku app data. You can also connect Heroku with marketing automation and sales enablement tools such as Hubspot, as well as replicate your data across multiple data warehouses, data lakes, and data marts as necessary.

How Can Help With Heroku and ETL


While the 5 Heroku ETL tips above are great ways to start integrating your Heroku app data, which ETL tool is best to use with Heroku? is a cutting-edge platform for building ETL and ELT data pipelines. The platform comes with a native Heroku Postgres connector, as well as more than 100 integrations with SaaS applications, databases, and analytics platforms. The user-friendly, drag-and-drop interface makes it easy for you to build robust, production-ready data pipelines from your Heroku database to a centralized data warehouse or data lake.

Ready to find out how can benefit your business? Get in touch with our team of data integration experts today for a chat about your business needs and objectives, or to start your 14-day pilot of the platform.