The cloud provides companies with a cheaper way of storing their data. The reason is that it saves them from having to purchase equipment and set up physical infrastructure for data storage. The cloud also relieves companies of the task of data management to ensure that it is well protected. Due to this, most companies prefer the cloud as the medium for data storage. When it comes to the field of Cloud Storage Management, the choice between S3 vs DynamoDB is a relatively tough one.

This article provides you with a comprehensive analysis of both cloud storage services and highlights the major differences between them to help you make the Amazon S3 vs DynamoDB decision with ease. It also provides you a brief overview of both cloud services along with their features.

Introduction to Amazon S3

Amazon S3 Logo

Amazon Simple Storage Service (Amazon S3) is a high-speed, scalable, web-based Cloud storage service. It was developed for backing up and archiving applications and data on AWS. 

S3 is a very useful product since it helps its users to store and retrieve data from any location on the web, any time they want. This is done via the AWS Management Console which provides an easy-to-use web interface. For instance, Amazon uses S3 to run its websites across the world. The popularity of S3 is growing at a high speed.

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Introduction to DynamoDB

DynamoDB Logo

The Amazon DynamoDB is a document and key-value database that offers its users a single-digit millisecond performance. It is a fully-managed, multi-active, multi-region, durable database that comes with built-in security, in-memory caching, backup and restore for internet-scale applications. It can handle 20 million requests per second and up to 10 trillion requests per day. 

Companies such as Airbnb, Toyota, Samsung, Lyft, and Capital One depend on the performance and scalability of DynamoDB to support their critical tasks. Learn 5 easy steps of connecting DynamoDB to S3.

Factors that Drive the Amazon S3 vs DynamoDB Decision

Now that you have a basic idea of both technologies let us attempt to answer the S3 vs. DynamoDB question. There is no one-size-fits-all answer here and the decision has to be taken based on the business requirements, budget, and parameters listed below. The following are the key factors that drive the S3 vs DynamoDB decision:

1) Category & Architecture

Amazon S3 is an object store good for the storage of large binary unstructured data. It can store objects of up to 5 TB in size. S3 groups the objects into buckets. See a bucket as a database table or a namespace or a disk drive. Each S3 bucket is associated with a region. It is easy to set up cross-region replication for quick local access and backups. It is difficult to set up multi-master replication in Amazon S3. The architecture of Amazon S3 is shown below.

Amazon S3 vs DynamoDB: Amazon S3 Architecture

DynamoDB is a document or NoSQL database. Although it can be used for the storage of binary objects, it was designed for the storage of structured textual/JSON data. It can store individual items of up to 400 KB in size. The items are stored in tables, which can be located in a particular region or replicated globally. The global tables support multi-master replication, allowing clients to write into the same item or table from multiple regions. The architecture of DynamoDB is shown below.

2) Purpose

Amazon S3 was designed for throughput, not predictable latency. It can handle an extremely high number of traffic requests, especially requests for different items. 

On the other hand, DynamoDB was designed for sustained usage patterns and low latency. For relatively small items, especially those with a size of less than 4 KB, DynamoDB runs individual operations faster than Amazon S3.DynamoDB can scale on-demand, but S3 offers better scalability. In case of huge volumes of traffic, DynamoDB can be overwhelmed for a while. 

3) Mode of Operation

Amazon S3 operations work on all the items. It is not possible to run atomic batch operations on object groups, and it’s hard to work only on parts of a particular object. However, there are restrictions to this, like retrieving byte ranges from an object, but it’s not easy to append content to a single object from many sources concurrently. 

DynamoDB works on structured documents; hence, its smallest atom of operation is the property inside an item. You can also store binary unstructured information in DynamoDB, but that is not its core use case. Multiple users can modify the properties of a structured document at the same time, or append to the same array. DynamoDB can handle conditional updates and batch operations, even atomic transactions on many items. 

4) Usefulness

Amazon S3 is more useful for extract transform load (ETL) data warehouse scenarios than for online or ad hoc queries. S3 also comes with services that allow for the querying of structured data within S3. However, this is slow compared to relational databases and S3. DynamoDB clearly understands the contents of items, and users can set up indexes to help them query the properties of items efficiently. 

5) Versioning

Amazon S3 supports automatic versioning, making it easy for users to track the history of changes and revert an object to its previous state. On the other hand, DynamoDB doesn’t support out of the box object versioning. Although users can implement this manually, it’s difficult to prevent old versions from being modified.

Limitations of Amazon S3

Although Amazon S3 is one of the popular cloud services of AWS, it does have some limitations. Some of them are:

  • New users may find it difficult to use its web console. 
  • It’s challenging to compose the security rules right. 
  • Amazon S3 can be costly depending on how you use it. 

Limitations of DynamoDB

Some of the limitations of DynamoDB include:

  • Poor monitoring can result in high costs. 
  • It’s only suitable for key-values operations. It doesn’t work well for relational operations. 
Integrate Amazon S3 to MySQL
Integrate Amazon S3 to Redshift
Integrate DynamoDB to PostgreSQL

Conclusion

This article gave a comprehensive analysis of the 2 popular cloud storage tools in the market today: Amazon S3 and DynamoDB. It gives a brief overview of both the cloud storage tools and their features and challenges. It also gave the parameters to judge each of the databases. Overall, the Amazon S3 vs DynamoDB choice solely depends on the goal of the company and the resources it has.

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Frequently Asked Questions

1. Is S3 faster than database?

Amazon S3 (Simple Storage Service) and traditional databases serve different purposes, and their performance metrics vary accordingly.

2. Why not use S3 as a database?

a) Lack of Structured Data Support
b) Query Capabilities
c) Latency and Performance

3. Why is DynamoDB better?

a) DynamoDB is designed for low-latency read and write operations, making it suitable for real-time applications.
b) It can handle high throughput and automatically scales to accommodate varying workloads without manual intervention.
c) DynamoDB provides high availability and durability through data replication across multiple AWS regions.

Nicholas Samuel
Technical Content Writer, Hevo Data

Nicholas Samuel is a technical writing specialist with a passion for data, having more than 14+ years of experience in the field. With his skills in data analysis, data visualization, and business intelligence, he has delivered over 200 blogs. In his early years as a systems software developer at Airtel Kenya, he developed applications, using Java, Android platform, and web applications with PHP. He also performed Oracle database backups, recovery operations, and performance tuning. Nicholas was also involved in projects that demanded in-depth knowledge of Unix system administration, specifically with HP-UX servers. Through his writing, he intends to share the hands-on experience he gained to make the lives of data practitioners better.