Amazon RDS vs Heroku Postgres: What are the differences?
Developers describe Amazon RDS as "Set up, operate, and scale a relational database in the cloud". Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call. On the other hand, Heroku Postgres is detailed as "Heroku's Database-as-a-Service. Based on the most powerful open-source database, PostgreSQL". Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.
Amazon RDS and Heroku Postgres are primarily classified as "SQL Database as a Service" and "PostgreSQL as a Service" tools respectively.
Some of the features offered by Amazon RDS are:
- Pre-configured Parameters
- Monitoring and Metrics
- Automatic Software Patching
On the other hand, Heroku Postgres provides the following key features:
- High Availability
"Reliable failovers" is the primary reason why developers consider Amazon RDS over the competitors, whereas "Easy to setup" was stated as the key factor in picking Heroku Postgres.
According to the StackShare community, Amazon RDS has a broader approval, being mentioned in 1437 company stacks & 526 developers stacks; compared to Heroku Postgres, which is listed in 74 company stacks and 39 developer stacks.
Considering moving part of our PostgreSQL database infrastructure to the cloud, however, not quite sure between AWS, Heroku, Azure and Google cloud. Things to consider: The main reason is for backing up and centralize all our data in the cloud. With that in mind the main elements are: -Pricing for storage. -Small team. -No need for high throughput. -Support for docker swarm and Kubernetes.
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While we initially started off running our own Postgres cluster, we evaluated RDS and found it to be an excellent fit for us.
The failovers, manual scaling, replication, Postgres upgrades, and pretty much everything else has been super smooth and reliable.
We'll probably need something a little more complex in the future, but RDS performs admirably for now.
We are using RDS for managing PostgreSQL and legacy MSSQL databases.
Unfortunately while RDS works great for managing the PostgreSQL systems, MSSQL is very much a second class citizen and they don't offer very much capability. Infact, in order to upgrade instance storage for MSSQL we actually have to spin up a new cluster and migrate the data over.
Stores the admin database for the SRX apps - includes an audit log, error tracking, and SRX admin message log.
Will also store PRS rules when refactor is complete.
Rock solid transactional storage of user, purchase and course activity data. During development database dumps were easy to create and download locally for testing.
We use heroku PostgreSQL databases for testing alongside our sandboxed application(s) in heroku.
Extremely simple, practically a one-click setup.
Our PostgreSQL servers, where we keep the bulk of Wirkn data, are hosted on the fantastically easy and reliable AWS RDS platform.
We use Aurora for our OLTP database, it provides significant speed increases on top of MySQL without the need to manage it
RDS allows us to replicate the development databases locally as well as making it available to CircleCI.
4 years of experience using Heroku Postgres for data storage and management.