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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.
We are building a social media app, where users will post images, like their post, and make friends based on their interest. We are currently using Cloud Firestore and Firebase Realtime Database. We are looking for another database like Amazon DynamoDB; how much this decision can be efficient in terms of pricing and overhead?
Hi, Akash,
I wouldn't make this decision without lots more information. Cloud Firestore has a much richer metamodel (document-oriented) than Dynamo (key-value), and Dynamo seems to be particularly restrictive. That is why it is so fast. There are many needs in most applications to get lightning access to the members of a set, one set at a time. Dynamo DB is a great choice. But, social media applications generally need to be able to make long traverses across a graph. While you can make almost any metamodel act like another one, with your own custom layers on top of it, or just by writing a lot more code, it's a long way around to do that with simple key-value sets. It's hard enough to traverse across networks of collections in a document-oriented database. So, if you are moving, I think a graph-oriented database like Amazon Neptune, or, if you might want built-in reasoning, Allegro or Ontotext, would take the least programming, which is where the most cost and bugs can be avoided. Also, managed systems are also less costly in terms of people's time and system errors. It's easier to measure the costs of managed systems, so they are often seen as more costly.
Pros of Amazon DynamoDB
- Predictable performance and cost62
- Scalable56
- Native JSON Support35
- AWS Free Tier21
- Fast7
- No sql3
- To store data3
- Serverless2
- No Stored procedures is GOOD2
- ORM with DynamoDBMapper1
- Elastic Scalability using on-demand mode1
- Elastic Scalability using autoscaling1
- DynamoDB Stream1
Pros of Mongoose
- Several bad ideas mixed together17
- Well documented17
- JSON10
- Actually terrible documentation8
- Recommended and used by Valve. See steamworks docs2
- Can be used with passportjs for oauth1
- Yeah1
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Cons of Amazon DynamoDB
- Only sequential access for paginate data4
- Scaling1
- Document Limit Size1
Cons of Mongoose
- Model middleware/hooks are not user friendly3
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