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Amazon DynamoDB vs Datomic Cloud: What are the differences?
Introduction
When considering database services for your application, it's important to understand the key differences between Amazon DynamoDB and Datomic Cloud. Both services offer scalable, reliable, and highly available solutions for different use cases. Here are the key differences between the two services:
Data Model: Amazon DynamoDB is a NoSQL database that uses a key-value and document data model, allowing for flexibility in storing different types of data. On the other hand, Datomic Cloud is a database that uses an entity-attribute-value model, providing a more structured approach to data storage.
Consistency Model: Amazon DynamoDB offers eventual consistency by default, with the option to choose strong consistency if required. In contrast, Datomic Cloud provides strong consistency out of the box, ensuring that all reads reflect the latest writes to the system.
Query Language: Amazon DynamoDB uses a proprietary query language and API for data retrieval and manipulation. Datomic Cloud, on the other hand, utilizes Datalog, a declarative query language that allows for expressive and powerful queries over the database.
Data Storage: Amazon DynamoDB is primarily designed for operational data storage, offering fast and predictable performance for read and write operations. Datomic Cloud, on the other hand, is optimized for transactional data storage, providing a full audit history of changes made to the data over time.
Scaling: Amazon DynamoDB allows for scaling by increasing read and write capacity units to meet the application's demands. Datomic Cloud, on the other hand, offers horizontal scaling by adding additional storage nodes to handle increased workload and storage requirements.
Data Security: Amazon DynamoDB provides encryption at rest and in transit to secure data stored in the database. Datomic Cloud offers fine-grained access control and audit logging to restrict access to sensitive data and track changes made to the database.
In Summary, understanding the key differences between Amazon DynamoDB and Datomic Cloud can help in choosing the right database service for your specific application requirements.
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 Datomic Cloud
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Cons of Amazon DynamoDB
- Only sequential access for paginate data4
- Scaling1
- Document Limit Size1
Cons of Datomic Cloud
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