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Amazon DynamoDB vs restdb.io: What are the differences?
Introduction
When comparing Amazon DynamoDB and restdb.io, it is important to note the key differences between the two database management systems.
Data Model: Amazon DynamoDB follows a NoSQL database model, specializing in key-value and document data, while restdb.io is based on a RESTful API model, offering a more flexible schema for data storage and retrieval.
Scalability: DynamoDB is fully managed by Amazon Web Services (AWS), allowing for seamless scaling of throughput and storage based on demand, while restdb.io offers scalable infrastructure but requires manual configuration for scaling needs.
Pricing: DynamoDB operates on a pay-per-usage pricing model, where users are charged based on the provisioned throughput capacity and storage used, while restdb.io has a subscription-based pricing model, which includes various tiers based on usage and features.
ACID Compliance: Amazon DynamoDB ensures ACID (Atomicity, Consistency, Isolation, Durability) compliance for data transactions, offering strong data consistency and durability, while restdb.io may not guarantee the same level of ACID compliance, depending on the nature of the RESTful API interactions.
Data Querying: DynamoDB offers powerful querying capabilities with secondary indexes and query optimization tools, allowing for efficient data retrieval, whereas restdb.io relies on RESTful API endpoints for data retrieval, which may not provide the same level of flexibility and optimization for complex queries.
Monitoring and Management: AWS provides comprehensive monitoring and management tools for DynamoDB, including metrics, alarms, and auto-scaling features, while restdb.io offers basic monitoring capabilities but may lack advanced management tools compared to a cloud-based service like DynamoDB.
In Summary, Amazon DynamoDB and restdb.io differ in their data models, scalability options, pricing structures, ACID compliance, data querying capabilities, and monitoring and management tools.
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 restdb.io
- Easy, yet powerful, db setup and management2
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Cons of Amazon DynamoDB
- Only sequential access for paginate data4
- Scaling1
- Document Limit Size1