Amazon DynamoDB Reviews

I use the solution for connecting API services with databases. At our company, Amazon DynamoDB is being used for data normalization and to configure JSON objects. 

The features of JSON documents and query handling of databases are vital features of the solution. 

The response time for data queries should be less than a second. The queried data is not required in normalization for parameter queries, password queries, or data that can be used frequently. 

It would be beneficial if the product can be made open source. 

I have been using Amazon DynamoDB for three years. 

The product is stable. 

The solution is highly scalable. 

I found the initial setup to be straightforward. I work with the graphic console and recently have been working with the APIs and queries of the Enterprise Command Line.

The ROI depends on how Amazon DynamoDB is integrated with other solutions. 

Amazon DynamoDB is an expensive product. 

I recommend that others use Amazon DynamoDB, but the expenditure must be calculated beforehand. I would rate the product an eight out of ten. 

The design approach of DynamoDB makes it very fast and scalable.

We have used most of the features offered by DynamoDB because the product is mature and they fit very well.

They are planning to introduce versioning in the future (http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/DynamoDBMapper.OptimisticLocking.html).

The application runs much faster and the query response time is three to five times faster when compared to Google Datastore.

The admin console is also very user friendly and provides hands-on features for the development team.

It provides good support for local development.

• The documentation could be refined to explain some basic topics better.
• The local DynamoDB version doesn't come with a tool to view the items inside the tables, so a third-party licensed product is required.
• An API to make the creation of complex queries with filters, limits, and offsets much easier is something to consider for future releases.
• Some things must be implemented manually and that takes a lot of time. At the same time, they are offered within the API in other NoSQL solutions.
• There is room for improvement of how the indexes are handled.
• An automated tool for increasing and decreasing the read/write capacity based on alarms would be welcomed.

We have been using the product for around six months.

There have been no stability issues. It works very well so far.

The design is based on key-value and offers great scalability and speed.

We have been using paid technical support during the development phase. I would give technical support a rating of 9/10.

They respond very fast and give good solutions, but sometimes they realize that it is a bug in the product and can't tell you when it will be fixed.

We used Google Datastore, but we switched to DynamoDB because we migrated to AWS.

The initial setup was straightforward.

Pricing is more complex than buying a license, so it depends on the products' needs.

We evaluated Microsoft Azure as a cloud solution, but in the end, we decided to go with AWS.

If you want a very fast NoSQL database, and you are willing to do some extra work in order to implement complex queries, DynamoDB is the way to go.

We have various use cases for the solution, including using it for IoT, messaging, etc.

The possibility of managing documents is the most valuable aspect of the solution. I like the fact that I don't have to define the fields. 

Features like the user interface and the pricing of the solution are also good.

Querying data on the solution is quite limited, but this is like any other NoSQL database. It's the most common criticism of the NoSQL database in general.

The solution is absolutely stable.

The solution is scalable.

The initial setup was straightforward. The deployment over DynamoDB services is a few seconds.

I implemented the solution myself.

We are using the public cloud deployment model.

I would rate the solution eight out of ten. I'm quite satisfied with the solution. Querying could always be better, but it's a typical complaint.