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Amazon DynamoDB vs Amazon EBS: What are the differences?
Introduction
Amazon DynamoDB and Amazon EBS are both storage services provided by Amazon Web Services (AWS) cloud platform. However, they have several key differences that make them suitable for different use cases. This article will highlight the major differences between Amazon DynamoDB and Amazon EBS.
Scalability: Amazon DynamoDB is a fully managed NoSQL database service that provides automatic scaling of resources to meet the demand of applications. It can handle massive workloads and scale up or down based on the traffic patterns. On the other hand, Amazon EBS is a block-level storage service that provides persistent storage volumes for EC2 instances. It allows you to provision storage volumes of different sizes, but it doesn't scale automatically like DynamoDB.
Data Model: Amazon DynamoDB is a NoSQL database service that uses a key-value store model. It allows you to store and retrieve any amount of data, and the data is organized based on primary key attributes. On the other hand, Amazon EBS provides block-level storage, which means it can store any type of data in blocks. It can be formatted with any file system and used like a physical hard drive.
Accessibility: Amazon DynamoDB is a fully managed service that is accessed through an API. It is designed to be highly available and fault-tolerant, with data automatically replicated across multiple availability zones. On the other hand, Amazon EBS volumes are accessed directly by EC2 instances. They are not replicated by default, but you can create snapshots of volumes for backup and recovery.
Latency: Amazon DynamoDB is designed for low-latency access to data, with response times in single-digit milliseconds. It is optimized for fast and predictable performance, making it suitable for real-time applications. On the other hand, Amazon EBS performance can vary based on the type of volume and the workload. While it provides good performance for most use cases, it may not be as fast as DynamoDB in terms of latency.
Pricing Model: Amazon DynamoDB pricing is based on the provisioned throughput and the amount of data stored. You pay for the amount of read and write throughput you provision, along with the storage used. On the other hand, Amazon EBS pricing is based on the volume type and the size of the storage. You pay for the provisioned storage capacity, regardless of the amount of data stored in the volume.
Use Cases: Amazon DynamoDB is often used for applications that require high scalability and low-latency access to data, such as gaming, ad tech, and IoT. It is also suitable for applications that need a flexible schema and can benefit from a fully managed service. On the other hand, Amazon EBS is commonly used for persistent storage requirements of EC2 instances, such as databases, file systems, and log files.
In summary, Amazon DynamoDB is a fully managed NoSQL database service that provides automatic scaling and low-latency access to data. It is optimized for high scalability and is suitable for applications that require fast and predictable performance. On the other hand, Amazon EBS is a block-level storage service that provides persistent storage for EC2 instances. It is suitable for applications that need a flexible storage solution and can benefit from direct access to block-level storage.
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 Amazon EBS
- Point-in-time snapshots36
- Data reliability27
- Configurable i/o performance19
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Cons of Amazon DynamoDB
- Only sequential access for paginate data4
- Scaling1
- Document Limit Size1
Cons of Amazon EBS
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