Item: Amazon DynamoDB
Rating: 9
Author: Verified User

Use Cases and Deployment Scope

It is a powerful NoSQL database service with several advantages, including scalability, high availability, and strong performance. As a 3rd Party Logistics company, we use it for various applications such as mobile apps with varying workloads, session management, handling of user profiles, shipment journey information, user behavior tracking, and in future we have plans to use it for IoT (Internet of Things) applications as well.

Pros and Cons

Scalability, as it can handle huge workloads with ease
Very low latency, millisecond latency for reads and writes
Robust security features
Feature of Global Tables
Backup and Restore features

Limited Query flexibility in comparison to SQL
Expensive for huge workloads
Complexity increases as workloads increased, making it difficult to optimize.
Data size limitations

Return on Investment

Better user experience analysis leading to better customer experience.
Better real-time visibility of analytics leading to reduced time to customer
Better data security leading to reduced data administration costs.

Scalability

I have taken one point away due to its size limits. In case the application requires queries, it becomes really complicated to read and write data. When it comes to extremely large data sets such as the case in my company, a third-party logistics company, where huge amount of data is generated on a daily basis, even though the scalability is good, it becomes difficult to manage all the data due to limits.

Performance

For us, it performs well in most of the regions. It surely provides a seamless experience as it has greatly helped in us providing real-time analysis on huge datasets which has greatly reduced time to customer which was not the case before. It is responsive at all scales for sure.

Alternatives Considered

MongoDB and Apache Cassandra

DynamoDB's scalability is more automated and effortless, making it easier to handle rapid growth. Other tools require more manual configuration while DynamoDB simplifies database administration. Also, DynamoDB provides strong consistency while other tools like MongoDB and Apache Cassandra provides Tunable consistency levels which can be both advantageous or disadvantageous as per your use case.

Key Insights

Do you think Amazon DynamoDB delivers good value for the price?

Yes

Are you happy with Amazon DynamoDB's feature set?

Yes

Did Amazon DynamoDB live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Amazon DynamoDB go as expected?

Yes

Would you buy Amazon DynamoDB again?

Yes

Other Software Used

Apache Spark, Apache Spark MLib, Amazon EMR (Elastic MapReduce), AWS Lambda, Amazon Elastic Compute Cloud (EC2), AWS Batch

Likelihood to Recommend

Amazon DynamoDB is well suited for scenarios where real-time analytics is needed on huge data, user profiles management, session management, IoT data storage, mobile applications, etc. It is not suited for scenarios where data sets are not huge, it is better to go for other options so as to avoid unnecessary costs. Also, it is not suitable for scenarios for your data size is exceeding the limit as that will force you to increase backend complexity. If your applications requires complex queries, DynamoDB's capability might be limited in this case as well.

Making better data decisions with Amazon DynamoDB

Overall Satisfaction with Amazon DynamoDB