We use Amazon DynamoDB to track account IDs, address ranges, and descriptions. It is primarily used to automate the process of maintaining our about 1,120 AWS accounts. We also use DynamoDB in production for a pretty large-scale product.
We are a data classification company. We classify non-structured data, like documents in the organization. When we classify a document, we store the document's name and severity in Amazon DynamoDB. If the document has a sensitive classification, we add a tag, which will connect with the company's CM so they can send that document out of the company. We store all the document data on Amazon DynamoDB.
Senior Engineering Consultant at ASSURANCE IQ, INC.
Real User
Top 5
2024-06-24T07:44:59Z
Jun 24, 2024
I use the solution in my company as a fast storage system. Since there are some serverless functions, we used to write the outcome of those into the Amazon DynamoDB. My company then used to receive it later from the other apps. It mostly does fast retrieval and acts as a good storage system.
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.
Solutions Architect at a tech services company with 501-1,000 employees
Real User
Top 20
2024-05-01T15:54:00Z
May 1, 2024
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.
There are actually several Amazon services related to Amazon Connect, a contact center solution. These include Amazon Connect, Lambda functions, Amazon DynamoDB, Amazon Kinesis, Amazon SNS, and Amazon SES. We use DynamoDB to manage our contact center dynamically. This requires the use of a DynamoDB table and Lambda functions.
DynamoDB is a NoSQL, cloud-based AWS service. It is a database service. It supports structured and unstructured data, providing flexibility similar to SQL and NoSQL databases. While AWS offers relational database services like RDS for structured data, DynamoDB handles unstructured data efficiently. It's designed for scalability and ease of use, allowing users to store and retrieve data quickly without predefined schemas or table creations. This flexibility extends to integrating software frameworks like LAMP, enabling seamless data sharing across applications.
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.
DynamoDB is suitable for a wide range of applications, from small-scale projects to large-scale and high-traffic applications. Amazon DynamoDB is a high-performance managed service, and AWS fully takes care of the operational parts, including hardware, setup, and maintenance.
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.
One of our customers has been using DynamoDB for four years. They are using it to store long strings of data, particularly experiences shared by people in nature domains, such as recreation zones. These experiences could be related to hiking, swimming, observing nature, or anything else. People can send in short messages, and those messages are stored in DynamoDB.
Database Architect at a transportation company with 1,001-5,000 employees
Real User
Top 10
2023-05-24T02:58:49Z
May 24, 2023
I use Amazon DynamoDB for EMR automation for EMR to run. Right? We have to configure everything on time since we have configurations on Amazon DynamoDB.
We use this solution for two main purposes. The first is for the IoT-H devices to collect data and push the collected data to the DynamoDB. The second aim is to use the Terraform integration for the GS. This solution supports 25 users.
The first use case was indexing large quantities of data streaming in from Kinesis so that we could look up the data and collect it for MapReduce jobs. Its current use case is as primary storage for a web-based service. It's a global data store for everything to do with content and customers. In terms of its version, it's hosted. There is no version. You just have DynamoDB.
We use Amazon DynamoDB to store data. We have a hardware device that is continuously reading data. For example, there is a sensor generating weather data every second, and we collect the data after 30 seconds. So, the data is quite huge. We store this data in DynamoDB. Depending on the client, we show some charts, etc. as well.
Amazon DynamoDB is a scalable NoSQL database valued for its speed and cost efficiency, adept in handling unstructured data and delivering fast data retrieval without predefined schemas.Amazon DynamoDB is recognized for seamless integration with AWS services and its ability to accommodate large datasets. It provides powerful performance with automatic scaling, JSON document storage, and requires no external configurations. Users appreciate the predictable performance and ease of use, although...
We use Amazon DynamoDB to track account IDs, address ranges, and descriptions. It is primarily used to automate the process of maintaining our about 1,120 AWS accounts. We also use DynamoDB in production for a pretty large-scale product.
We are a data classification company. We classify non-structured data, like documents in the organization. When we classify a document, we store the document's name and severity in Amazon DynamoDB. If the document has a sensitive classification, we add a tag, which will connect with the company's CM so they can send that document out of the company. We store all the document data on Amazon DynamoDB.
I use the solution in my company as a fast storage system. Since there are some serverless functions, we used to write the outcome of those into the Amazon DynamoDB. My company then used to receive it later from the other apps. It mostly does fast retrieval and acts as a good storage system.
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.
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.
We use the solution to emulate MongoDB for the document database.
There are actually several Amazon services related to Amazon Connect, a contact center solution. These include Amazon Connect, Lambda functions, Amazon DynamoDB, Amazon Kinesis, Amazon SNS, and Amazon SES. We use DynamoDB to manage our contact center dynamically. This requires the use of a DynamoDB table and Lambda functions.
DynamoDB is a NoSQL, cloud-based AWS service. It is a database service. It supports structured and unstructured data, providing flexibility similar to SQL and NoSQL databases. While AWS offers relational database services like RDS for structured data, DynamoDB handles unstructured data efficiently. It's designed for scalability and ease of use, allowing users to store and retrieve data quickly without predefined schemas or table creations. This flexibility extends to integrating software frameworks like LAMP, enabling seamless data sharing across applications.
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.
Amazon DynamoDB is used to store data in the form of JSON. I use AWS Lambda to insert data into Amazon DynamoDB.
Since Amazon DynamoDB is a serverless NoSQL database, we are using it to develop an application that uses a NoSQL database.
DynamoDB is suitable for a wide range of applications, from small-scale projects to large-scale and high-traffic applications. Amazon DynamoDB is a high-performance managed service, and AWS fully takes care of the operational parts, including hardware, setup, and maintenance.
We use the product to store historical data.
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.
One of our customers has been using DynamoDB for four years. They are using it to store long strings of data, particularly experiences shared by people in nature domains, such as recreation zones. These experiences could be related to hiking, swimming, observing nature, or anything else. People can send in short messages, and those messages are stored in DynamoDB.
It does the basic stuff. It's an efficient resource, just like a special database.
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.
I use Amazon DynamoDB for EMR automation for EMR to run. Right? We have to configure everything on time since we have configurations on Amazon DynamoDB.
We use Amazon DynamoDB because we require a non-relational database for a variety of brands.
We use this solution for two main purposes. The first is for the IoT-H devices to collect data and push the collected data to the DynamoDB. The second aim is to use the Terraform integration for the GS. This solution supports 25 users.
The first use case was indexing large quantities of data streaming in from Kinesis so that we could look up the data and collect it for MapReduce jobs. Its current use case is as primary storage for a web-based service. It's a global data store for everything to do with content and customers. In terms of its version, it's hosted. There is no version. You just have DynamoDB.
We use Amazon DynamoDB to manage our localization data.
We use Amazon DynamoDB to store data. We have a hardware device that is continuously reading data. For example, there is a sensor generating weather data every second, and we collect the data after 30 seconds. So, the data is quite huge. We store this data in DynamoDB. Depending on the client, we show some charts, etc. as well.
We are using Amazon DynamoDB for our company for multiple service database management.
I am currently using it for proof of concept and testing out its capabilities. We are publishing the IoT data on DynamoDB. We have its latest version.
We have various use cases for the solution, including using it for IoT, messaging, etc.