Apache Aurora vs Microsoft SQL Server: What are the differences?
Developers describe Apache Aurora as "An Apcahe Mesos framework for scheduling jobs, originally developed by Twitter". Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation. 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.
Apache Aurora can be classified as a tool in the "Cluster Management" category, while Microsoft SQL Server is grouped under "Databases".
Apache Aurora is an open source tool with 616 GitHub stars and 231 GitHub forks. Here's a link to Apache Aurora's open source repository on GitHub.
According to the StackShare community, Microsoft SQL Server has a broader approval, being mentioned in 478 company stacks & 443 developers stacks; compared to Apache Aurora, which is listed in 6 company stacks and 3 developer stacks.
What is Apache Aurora?
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
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.
Main transactional database. SQL Server 2012 Enterprise with AlwaysOn Availability Groups for high availability and disaster recovery.