Amazon SQS vs Heroku Postgres

Amazon SQS vs Heroku Postgres: What are the differences?

Developers describe Amazon SQS as "Fully managed message queuing service". Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use. 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 SQS can be classified as a tool in the "Message Queue" category, while Heroku Postgres is grouped under "PostgreSQL as a Service".

Some of the features offered by Amazon SQS are:

• A queue can be created in any region.
• The message payload can contain up to 256KB of text in any format. Each 64KB ‘chunk’ of payload is billed as 1 request. For example, a single API call with a 256KB payload will be billed as four requests.
• Messages can be sent, received or deleted in batches of up to 10 messages or 256KB. Batches cost the same amount as single messages, meaning SQS can be even more cost effective for customers that use batching.

On the other hand, Heroku Postgres provides the following key features:

• High Availability
• Rollback
• Dataclips

"Easy to use, reliable" is the top reason why over 45 developers like Amazon SQS, while over 27 developers mention "Easy to setup" as the leading cause for choosing Heroku Postgres.

According to the StackShare community, Amazon SQS has a broader approval, being mentioned in 384 company stacks & 103 developers stacks; compared to Heroku Postgres, which is listed in 74 company stacks and 39 developer stacks.