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Azure Cosmos DB vs Microsoft SQL Server: What are the differences?
What is Azure Cosmos DB? A fully-managed, globally distributed NoSQL database service. Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.
What is Microsoft SQL Server? 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.
Azure Cosmos DB belongs to "NoSQL Database as a Service" category of the tech stack, while Microsoft SQL Server can be primarily classified under "Databases".
"Best-of-breed NoSQL features" is the top reason why over 13 developers like Azure Cosmos DB, while over 134 developers mention "Reliable and easy to use" as the leading cause for choosing Microsoft SQL Server.
According to the StackShare community, Microsoft SQL Server has a broader approval, being mentioned in 478 company stacks & 443 developers stacks; compared to Azure Cosmos DB, which is listed in 24 company stacks and 24 developer stacks.
What is Azure Cosmos DB?
What is Microsoft SQL Server?
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Why do developers choose Microsoft SQL Server?
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What are the cons of using Azure Cosmos DB?
What are the cons of using 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.
If you need a document-based database with geo-redundancy (imagine AU-HU distance), this is the way to go.