Amazon EMR vs Heroku Postgres: What are the differences?
Developers describe Amazon EMR as "Distribute your data and processing across a Amazon EC2 instances using Hadoop". Amazon EMR is used in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. Customers launch millions of Amazon EMR clusters every year. 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 EMR can be classified as a tool in the "Big Data as a Service" category, while Heroku Postgres is grouped under "PostgreSQL as a Service".
Some of the features offered by Amazon EMR are:
- Elastic- Amazon EMR enables you to quickly and easily provision as much capacity as you need and add or remove capacity at any time. Deploy multiple clusters or resize a running cluster
- Low Cost- Amazon EMR is designed to reduce the cost of processing large amounts of data. Some of the features that make it low cost include low hourly pricing, Amazon EC2 Spot integration, Amazon EC2 Reserved Instance integration, elasticity, and Amazon S3 integration.
- Flexible Data Stores- With Amazon EMR, you can leverage multiple data stores, including Amazon S3, the Hadoop Distributed File System (HDFS), and Amazon DynamoDB.
On the other hand, Heroku Postgres provides the following key features:
- High Availability
- Rollback
- Dataclips
"On demand processing power" is the top reason why over 13 developers like Amazon EMR, while over 27 developers mention "Easy to setup" as the leading cause for choosing Heroku Postgres.
According to the StackShare community, Heroku Postgres has a broader approval, being mentioned in 74 company stacks & 38 developers stacks; compared to Amazon EMR, which is listed in 93 company stacks and 18 developer stacks.