Amazon DynamoDB Reviews

We use the solution to handle structured data. So, whenever you need to make a runtime call and send any data, you can create it. To store the data exclusively, we need to use granularity. You must integrate with Lambda to process and store the records, whether they're coming from Connect or elsewhere.

The most unbelievable feature is NoSQL. Unlike traditional SQL databases, DynamoDB doesn't require predefined schemas. You don't have to design the schema, which can be limiting in SQL databases. Additionally, in SQL databases, modifying the schema to add new columns can be confusing and must be done before adding new data. DynamoDB allows for flexibility in adding new attributes to your data at runtime without altering the schema. This makes data processing more efficient and customizable. The performance of DynamoDB is highly configurable, depending on the provisioned Read Capacity Units and Write Capacity Units that you allocate to your tables.

The solution could be cheaper.

I have been using Amazon DynamoDB for 6 years.

The solution doesn't break down.

The availability is very good. It is also scalable.

The solution is expensive.

DynamoDB is one of the services that 90% of people use on AWS.

Let's say we are developing an application using AWS. For the backend data storage, DynamoDB is the best solution AWS offers for NoSQL databases. If SQL is needed, then RDS is the way to go.

You must understand the basic CRUD operations of databases, along with the APIs. Knowing how to create a schema, determining primary and foreign keys is essential. The AWS documentation provides detailed guidance on these.

DynamoDB supports multiple areas and has good monitoring and security features. AWS CloudWatch can be used for monitoring, and third-party tools like Datadog or additional integration are available for functionality.

Overall, I rate the solution a nine out of ten.

Amazon DynamoDB is used to store data in the form of JSON. I use AWS Lambda to insert data into Amazon DynamoDB.

In a relational database like MySQL, we convert values, like name, age, or other details about a person, into tables. We directly pass the JSON value to Amazon DynamoDB, which is why Amazon DynamoDB is faster than relational databases.

The solution's efficiency and performance should be faster than other databases.

I have been using Amazon DynamoDB for six months.

I rate the solution a nine out of ten for stability.

Amazon DynamoDB is a scalable solution that can store more data than other databases. AWS manages Amazon DynamoDB, such as increasing the storage, RAM, or CPU of its actual server. We need not worry about the solution's scalability. The solution's availability is 24/7.

The solution’s technical support is good.

I previously used Amazon RDS.

The solution’s initial setup is easy.

We can deploy Amazon DynamoDB in one to two hours.

The solution was free to use one month ago, but now it is a paid service. Amazon DynamoDB is not an expensive solution.

We can use Amazon DynamoDB for both on-premises and in the cloud.

Overall, I rate the solution a seven out of ten.

We use Amazon DynamoDB because we require a non-relational database for a variety of brands.

For example, we have extensive experience with relational databases. If you use Dynamo to implement a large project, it will help you implement it faster and perform faster searches. It's good because I feel, the JSON format makes it easier to read.

The most valuable feature of this solution is the non-relational database.

If you have no prior experience with this type of non-relational database, the syntaxes, implementation, or understanding may be difficult.

I have been using Amazon DynamoDB for one year.

I am working with the latest version.

Amazon DynamoDB is quite stable.

Amazon DynamoDB is a scalable solution.

We have 160 users, in our organization.

We need to build a better solution using this database. Perhaps for future items. That was a great experience.

I would rate the technical support a four out of five.

Previously, we used CatalinaDB. It is very similar.

If you don't have any prior expertise, it may be rather complex.

We only require one person who has knowledge of databases to maintain this solution.

The deployment was done in-house.

We have seen an ROI, but the pricing is actually determined by the clients you implement.

It is a little expensive. 

It is dependent on the license you use. The license we now have is for the consumption of reading. It's around $80 each month, or more.

We tried to implement certain schemes or determine what is the best way to implement the project. We discovered that Dynamo was better.

Have database experience not just in relational databases, but also in non-relational databases, as well as AWS or configuration experience.

I would rate Amazon DynamoDB a nine out of ten.

The solution is being used for scaling. For instance, if your throughput is X, then automatically, we can handle two X without incurring any additional cost, which gives you leverage over the spiking nature of the customer.

The latency feature is precious.

The setup cost could be reduced. But overall, the tool works smoothly.

I have been using Amazon DynamoDB for the last two years. 

Amazon DynamoDB is a managed database by AWS, so it handles scalability. I've seen improvements in scalability. For customer data, they replicate it three times independently of use, ensuring they can handle peak throughput at twice the usual rate. From a cost perspective, I'm charged based on the amount of data scanned and returned.

It provides premium support for enterprise solutions and real-time assistance.

Positive

Integration with Amazon DynamoDB is straightforward due to clear documentation and comprehensive support. 

Investing in Amazon DynamoDB has provided us with reliability and scalability, which are crucial for our operations. This has been a significant return on our investment.

It is costly. To reduce the costs, users need to read the node in front of it. For read-heavy groups, cache optimization can help manage costs. I can't disclose specific pricing, but it's competitive compared to others in the market, and this information is easily accessible online.

Amazon DynamoDB stands out primarily in its managed database feature compared to other tools. While other tools like MongoDB offer similar support, DynamoDB excels in its GSI and LSI capabilities, especially in partitioning and data handling. Its reliability and security features are notable, meeting our company's data security requirements.

I would rate Amazon DynamoDB an eight out of ten, primarily for its reliability, scalability, and security features. In terms of support, I would rate it above nine, especially for enterprise solutions with premium backing that ensures real-time assistance.

DynamoDB doesn't directly support AI-driven applications, but it can certainly be used as a backend database for such applications.

I would rate Amazon DynamoDB an eight out of ten, primarily for its reliability, scalability, and security features.

We use the product as our database. It is a NoSQL database. We can use DynamoDB as our database if we don't need SQL.

The best feature of the solution is that it is a NoSQL database. Many tables make a database. When we define a table, we have to define the schema of the table. For NoSQL databases, we don't need to define it. The table accepts any input. Each row will have its own column. We do not have to define the columns in advance. We can add columns to each row and push the data. We can query as much as we want.

SQL databases exist to speed up the queries. This advantage is not present in NoSQL databases. We must query databases very fast. To help with the process, the product provides secondary indexes. Secondary indexes are a copy of the table. The table is constructed in such a way that it can be used to support one query. Whenever we query a particular item, if we give the name of the secondary index in the query, the query will be faster.

The solution supports around 20 global secondary indexes. We can just create a table without thinking about its format. When our application develops, we will have more and more queries to do. We might realize later that the initial table does not support the query and that we have to change the schema of the table. To do so, we will have to change the structure of the entire table for one query. In DynamoDB, when we encounter a new query, we can just create a new secondary index for that to an existing table. We wouldn’t have to modify the main table. The query will be fast when we query the secondary index, which is a copy of the main table. Through the production process, we don't have to be concerned about modifying the main table.

The product allows us to query for items in the UI. Sometimes when we query through the UI, it takes a long time to get the results. I would like it if the results were faster.

My organization has been using the solution for more than one year.

The product is stable. We have had no issues. We always get the data.

The solution is scalable. Around four people were using the product before. Now, only two people use it in the organization.

We were using MongoDB. It was outside AWS, and we wanted to get everything inside AWS. So we chose DynamoDB. I prefer DynamoDB over MongoDB.

The solution is deployed on the cloud. The initial setup is very easy.

If we go through the main DynamoDB, it will be a scan operation. It will scan through each record. If we set up a secondary index for a particular query type, we can get it fast. It is the fastest way to get it.

In a normal database, if we launch something into production and want to add one more feature, but the feature needs an additional query, and the existing table cannot perform the query fast, we will have to remodel the entire table. It will interrupt the process. In DynamoDB, we can just add one more secondary index and route that query to the secondary index.

If someone wants to use the solution, they should go ahead. It is as good as anything else. Overall, I rate the product a nine out of ten.

Personally, I use DynamoDB for creating my Proof of Concepts (POCs) for testing DynamoDB functionalities. It's not used extensively by me but is likely used by the database team.

DynamoDB is easy to configure, easy to use, and allows for writing data in JSON format.

I have not used it extensively at a larger scale, so I cannot provide feedback on improvements.

I have been using DynamoDB for about four years.

I haven't used DynamoDB in large volume, so I haven't faced any stability issues during my usage.

I haven't used DynamoDB for large scale data handling. I've used other solutions like MongoDB and S3 for such purposes.

Support is better if using a paid version. I gave the support a rating of seven out of ten.

Neutral

I have used other resources like MongoDB and S3 for handling large-scale data.

I would recommend DynamoDB to other people.

I'd rate the solution eight out of ten.

I work in the cloud automation domain. I used the product to store data related to automation. We had our own website. We use the product to manage automation. I also used it to store user information.

The solution is very simple to use. It is a NoSQL database. The UI is good. DynamoDB Streams is an amazing feature. If there are any changes in the DB, it will automatically trigger the workflow. The GUI is awesome.

I have used the solution in the past year.

I rate the tool’s stability a ten out of ten. It worked perfectly for us.

I rate the tool’s scalability a ten out of ten. We had more than 500 users.

I used MongoDB a very long time ago.

The initial setup is easy. The documentation is good. The deployment could be done within minutes.

The solution is cheaper than Cosmos DB. If an organization doesn’t have much data to store, they can use the solution for free.

It is a good investment. We were able to use it in automation. It was easy to use. Even the new joiners were able to use it effectively. All our automation was effectively stored, and we could build the dashboard out of it to present to the higher management. Anyone who wants to explore a NoSQL database in the cloud must use DynamoDB. Overall, I rate the product a ten out of ten.

We have enabled a state-locking mechanism in Terraform, so we store our keys in DynamoDB. 

If the database is kept running continuously, extra costs will be incurred. This particular area needs enhancement.

I rate the platform's stability a nine out of ten.

I rate the platform's scalability a nine out of ten.

The technical support team is always available to help us.

Positive

I worked with MongoDB and Firebase earlier. I switched to DynamoDB because of the company and client requirements. Atlassian and Google already own the other two services. I used MongoDB for a machine learning project and Firebase for an Android-level project.

The initial setup process is easy.

I have yet to use DynamoDB for real-time data processing in my applications. However, in Terraform, we utilized it to create multiple infrastructures. Terraform has a state-locking feature, which prevents simultaneous data updates from multiple users. For example, triggering a data update one minute before you do will lock your access until my update is completed. We implemented this feature for telco data monitoring purposes.

Data modeling in DynamoDB is simple and easy to use in our cases. You have primary and secondary tables, and then you can easily model the data. Whatever you use to access the non-structural data is how you get the storage, i.e., API gateways, workflows, and microservices that need to communicate with each other. This is where the database comes into the picture.

I advise others to be thoughtful and careful when using the platform because if you keep the database running continuously, it might cost you a lot of money. 

I recommend Amazon DynamoDB to others and rate it a nine out of ten.