Amazon DynamoDB vs Mongoose: What are the differences?
What is Amazon DynamoDB? Fully managed NoSQL database service. All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
What is Mongoose? MongoDB object modeling designed to work in an asynchronous environment. Let's face it, writing MongoDB validation, casting and business logic boilerplate is a drag. That's why we wrote Mongoose. Mongoose provides a straight-forward, schema-based solution to modeling your application data and includes built-in type casting, validation, query building, business logic hooks and more, out of the box.
Amazon DynamoDB and Mongoose are primarily classified as "NoSQL Database as a Service" and "Object Document Mapper (ODM)" tools respectively.
"Predictable performance and cost" is the top reason why over 53 developers like Amazon DynamoDB, while over 14 developers mention "Well documented" as the leading cause for choosing Mongoose.
Mongoose is an open source tool with 19K GitHub stars and 2.63K GitHub forks. Here's a link to Mongoose's open source repository on GitHub.
According to the StackShare community, Amazon DynamoDB has a broader approval, being mentioned in 444 company stacks & 187 developers stacks; compared to Mongoose, which is listed in 88 company stacks and 92 developer stacks.
What is Amazon DynamoDB?
What is Mongoose?
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I use Amazon DynamoDB because it integrates seamlessly with other AWS SaaS solutions and if cost is the primary concern early on, then this will be a better choice when compared to AWS RDS or any other solution that requires the creation of a HA cluster of IaaS components that will cost money just for being there, the costs not being influenced primarily by usage.
I inherited a stack where Mongoose is used in the database layer.
It's been several months and it's still the single highest source of daily WT*s in my backend development. The API is full of irregularities and the design is a poor mix of object-orientation and stateful objects with a lot implicit behavior. Mongoose made the choices of taking the worst parts of ORMs and using them in a context where the benefits of ORMs don't apply. The only reason I'm keeping it is its handy
.populate() feature. Expect bad surprises!
For most of the stuff we use MySQL. We just use Amazon RDS. But for some stuff we use Amazon DynamoDB. We love DynamoDB. It's amazing. We store usage data in there, for example. I think we have close to seven or eight hundred million records in there and it's scaled like you don't even notice it. You never notice any performance degradation whatsoever. It's insane, and the last time I checked we were paying $150 bucks for that.
zerotoherojs.com ’s userbase, and course details are stored in DynamoDB tables.
The good thing about AWS DynamoDB is: For the amount of traffic that I have, it is free. It is highly-scalable, it is managed by Amazon, and it is pretty fast.
It is, again, one less thing to worry about (when compared to managing your own MongoDB elsewhere).
We store customer metadata in DynamoDB. We decided to use Amazon DynamoDB because it was a fully managed, highly available solution. We didn't want to operate our own SQL server and we wanted to ensure that we built CloudRepo on high availability components so that we could pass that benefit back to our customers.
몇몇 로그는 현재 AWS DynamoDB 에 기록되고 있습니다. 개선을 통해 mongodb 로 옮길 계획을 하고 있습니다. 아주 간단한 데이터를 쌓는 용도로는 나쁘지 않습니다. 다만, 쿼리가 아주 제한적입니다. 사용하기 전에 반드시 DynamoDB 의 스펙을 확인할 필요가 있습니다.
To store device health records as it allows super fast writes and range queries.