Heroku Postgres vs Microsoft SQL Server: What are the differences?
Developers describe Heroku Postgres 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. On the other hand, Microsoft SQL Server is detailed as "A relational database management system developed by Microsoft". Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
Heroku Postgres belongs to "PostgreSQL as a Service" category of the tech stack, while Microsoft SQL Server can be primarily classified under "Databases".
"Easy to setup" is the primary reason why developers consider Heroku Postgres over the competitors, whereas "Reliable and easy to use" was stated as the key factor in picking Microsoft SQL Server.
According to the StackShare community, Microsoft SQL Server has a broader approval, being mentioned in 470 company stacks & 425 developers stacks; compared to Heroku Postgres, which is listed in 74 company stacks and 38 developer stacks.
What is Heroku Postgres?
What is Microsoft SQL Server?
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We initially started out with Heroku as our PaaS provider due to a desire to use it by our original developer for our Ruby on Rails application/website at the time. We were finding response times slow, it was painfully slow, sometimes taking 10 seconds to start loading the main page. Moving up to the next "compute" level was going to be very expensive.
We moved our site over to AWS Elastic Beanstalk , not only did response times on the site practically become instant, our cloud bill for the application was cut in half.
In database world we are currently using Amazon RDS for PostgreSQL also, we have both MariaDB and Microsoft SQL Server both hosted on Amazon RDS. The plan is to migrate to AWS Aurora Serverless for all 3 of those database systems.
Additional services we use for our public applications: AWS Lambda, Python, Redis, Memcached, AWS Elastic Load Balancing (ELB), Amazon Elasticsearch Service, Amazon ElastiCache
I could spin up an Amazon EC2 instance and install PostgreSQL myself, review latest configuration best practices, sort Amazon EBS storage for data, set up a snapshot process etc.
Alternatively I could use Amazon RDS, Amazon RDS for PostgreSQL or Heroku Postgres and have most of that work handled for me, by a team of world experts...
We've always counted on SQL Server as our database backend. It has served us well over the years. It isn't the cheapest part of our stack, but with the plethora of tools provided by 3rd parties, we have found an incredible and scalable method of keeping our data available and easy to maintain.
Defacto, industry standard for backend relational databases. Entity Framework makes designing, migrating & maintaining SQL Server databases a breeze. LocalDB is especially helpful during development.
Our core systems that we integrate with are using SQL Server 2012 / 2016 database servers. We use database views on core system databases to help build our domain model.
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.
Main transactional database. SQL Server 2012 Enterprise with AlwaysOn Availability Groups for high availability and disaster recovery.
4 years of experience using Heroku Postgres for data storage and management.
Created several tables for users, brands, deals, campaigns, and tracking.