![]() To migrate data from one Postgres instance to another, you'll need access to the Postgres command line tools. If you're interested in detailed instructions, check out my post on Hashnode. Setting this up is outside of the scope of this article. The data set I used is food data from the United States Department of Agriculture. Prerequisitesįor this walk-through, I set up a Heroku app with a PostgreSQL database and loaded some sample data. How to migrate from Heroku Postgres to AWSįortunately, migrating from Heroku Postgres to AWS is a fairly painless process, although it does involve some coordination. Given these drawbacks, it's little wonder some teams who started small on Heroku would be looking to jump ship to AWS. Unfortunately, there is no way to resolve this, as Heroku does not grant superuser access to PostgreSQL on any of its plans. This means that some PostgreSQL operations - such as creating new types and functions - aren't allowed. Heroku limits you to an access level "one step below the superuser", in their own words. Some operations in PostgreSQL require you to have root, or superuser, access to perform certain operations. With its limited regional reach and services (like Heroku Postgres) that rely on storage in US data centers, Heroku can't meet many - if any - of those requirements. Dozens of countries globally have enacted laws that require some or all data on its citizens be kept within a country's borders. That makes it less attractive for teams servicing a global user base.ĭata residency. Heroku offers two "regions": The US and Europe. AWS supports spinning up compute in 20+ regions around the world. At TinyStacks, for example, we create all Amazon RDS instances for our customer's stacks in a private subnet for enhanced security. You can create much more secure architectures directly on AWS. Heroku Postgres instances are publicly reachable on the Internet. (That's not surprising - Heroku is using AWS itself and simply charging an overhead for its ease of use!) While Heroku's pricing is easier to calculate, it tends to be more expensive than what you can get with a carefully managed offering on a cloud provider. As I discussed previously, Heroku's pre-packaged offerings generally don't provide as much compute capacity as is available on a cloud provider such as AWS. When it comes to Postgres, Heroku falls short on several fronts: So it's not surprising that many teams go with Heroku for their initial launch.īut, as I also discussed last time, using Heroku has significant downsides as well. Heroku brings these upsides to its Postgres hosting offering as well. By contrast, Heroku offers all-in-one pricing packages that make cloud spend predictable and easy to estimate. This complexity makes it hard for teams to predict exactly how much they'll spend month over month. ![]() AWS pricing for individual products often involves multiple factors like usage and data transfer rates. Second, Heroku's pricing model is straightforward. Heroku's feature set is clean and often much easier to use than their AWS counterparts. AWS tends to overwhelm users with features. I touched on some of the reasons why in my last post on Heroku.įirst, Heroku is simple to use and understand. Heroku is the go-to platform for many development teams just beginning their journey into the cloud. ![]() I'll also detail the steps to migrate from Heroku Postgres to AWS, some obstacles you might face, and some tricks for easing your migration path. In this article, I'll discuss why many teams are making this jump. However, over time, a significant number find themselves migrating their Postgres workloads over to AWS. Many teams host their relational data storage on Heroku.
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