Last year I wrote a post comparing the data services offered by both AWS and Microsoft Azure. Well, there’s been some changes since, so it was time to provide an updated graphic and links.
Since both Microsoft Azure and Amazon Web Services offer many data services, I thought it worth the time to create a graphic to help everyone understand the services a bit more. Essentially, I wanted to build a cheat sheet for any data services comparison (click to embiggen):
You might notice that there is no Data Warehouse category. That category is located in the Analytics and Big Data comparison chart which I will share in a future post.
It is my hope that this post will be a starting guide for you when you need to research cloud data services. I’m not going to do a feature comparison here because these systems evolve so quickly I’d spend all day updating the info. Instead, you get links to the documentation for everything and you can do your own comparisons as needed. I hope to have future posts that help break down features and costs, but for now let’s keep it simple.
Relational
Azure offerings: SQL Database, Database for MySQL, Database for PostgreSQL, Database for MariaDB
RDS is an umbrella term, as it is six engines in total, and it includes Amazon Aurora, MySQL, MariaDB, Oracle, Microsoft SQL Server, and PostgreSQL. I’ve listed Aurora as a distinct offering because it is the high-end service dedicated to MySQL and PostgreSQL. Since Azure also offers those distinct services it made sense to break Aurora out from RDS. (Or, to put it another way, if I didn’t call out Aurora here you’d finish this post and say ‘what about Aurora’, and now you don’t have to ask that question.)
NoSQL – Key/Value
Azure offerings: Cosmos DB, Table Storage
AWS offerings: DynamoDB, SimpleDB
Cosmos DB is the major NoSQL player for Azure, as it does everything (key/value, document, graph) except relational. DynamoDB is a workhorse for AWS. SimpleDB is still around, but there are rumors it will be going away. This might be due to the fact that you cannot create a SimpleDB service using the AWS Console. So, short story, look for this category to be just Cosmos DB and DynamoDB in the future.
NoSQL – Document
Azure offerings: Cosmos DB
AWS offerings: DocumentDB
Azure used to offer DocumentDB, but that platform was sunset when Cosmos DB came alive. AWS recently launched DocumentDB with MongoDB compatibility in what some people see as a major blow to open source.
NoSQL – Graph
Azure offerings: Cosmos DB
AWS offerings: Neptune
As of May 2019, Neptune is in Preview, so the documentation is likely to change in the coming weeks months years (well, that’s my assumption, because Neptune has been in Preview since November 2018.) Cosmos DB uses a Gremlin API for graph purposes.
In-Memory
Azure offerings: Cache for Redis
AWS offerings: ElastiCache
Both of these services are built upon Redis, so the real question here is if you want to use Redis-as-a-service from a 3rd party provider as opposed to just using it Redis itself.
Time Series
Azure offerings: Time Series Insights
AWS offerings: Timestream
If you are in need of a time series database for your IoT collections, then both Azure and AWS have a service to offer. Azure Time Series Insights was launched in early 2017, and AWS announced Timestream in late 2018. In other words, the world of data services is moving fast, and the two major cloud providers are able to roll out services to meet growing demand.
Ledger
Azure offerings: [Sad Trombone]
AWS offerings: Quantum ledger Database
Setting aside the silliness of using the buzzword ‘Quantum’ in the name of this product, AWS does have a ledger database service available. As of May 2019, Azure does not offer a similar service.
Pricing
Azure Pricing calculator: https://azure.microsoft.com/en-us/pricing/calculator/
AWS Pricing Calculator: https://calculator.aws
I like using pricing as a way to start any initial comparison between data services. These calculators will help you focus on the important details. Not just costs, but how the technology works. For example, Azure SQL Database focuses on the concept of a DTU, which has no meaning in AWS. Using the calculators forces you to learn the differences between the two systems. It’s a great starting point.
That being said, trying to compare the data services offered by AWS and Azure can be frustrating. Part of me thinks this is done on purpose by both companies in an effort to win our favor without giving away more information than is necessary. This is a common practice, and I’m not bashing either company for doing what has been done for centuries. I’m here to help others figure out how to make the right choice for their needs. At the end of the day, I believe both Amazon and Microsoft want the same thing: happy customers.
By starting at the pricing pages I can then dive into the specific costs, and use that as a first level comparison between the services. If you start by looking at resource limits and maximums you will spend a lot of time trying to compare apples to oranges. Just focus on costs, those resources, throughput, and DR. That should be a good start to help you determine the cost, benefit, and risk of each service.
Summary
I hope you find this page useful for referencing the many data service offerings from both Microsoft Azure and Amazon Web Services. I will do my best to update this page as necessary, and offer more details and use cases as I am able.
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