Senior Principal at a hospitality company with 10,001+ employees
Real User
Top 10
Aug 11, 2025
We use Amazon DocumentDB; there are quite a few use cases we have solved with AWS components. The primary use case is that of a data lake, and we use S3 primarily for lake purposes, along with other services such as Lambda, SQS, and SNS. There is use of Amazon DocumentDB, but for a different use case, not the primary data lake use case. Regarding Amazon DocumentDB, I have been working with it for approximately three to three and a half years. One primary reason we chose Amazon DocumentDB on AWS is its ability to handle unstructured data, such as PDFs. There's a significant amount of user manuals and documentation related to operational handbooks that we upload into Amazon DocumentDB, and the primary purpose is to make those easily searchable.
I support my customers with Amazon DocumentDB. Amazon DocumentDB is a nice product when using it for smaller registers about websites or when tabular information is needed. Yesterday, I attended to a customer at the end of my workday. This customer has a concentrated database where invoices, orders, bills, and all registers are concentrated on Amazon DocumentDB.
We use it in a few ways. Sometimes it functions as a cache for quick lookups using scans. Other times, DocumentDB serves as a complete backend. For example, we built the entire backend of one of our healthcare applications for Sweden using DocumentDB. We store patient records, medical information... everything runs on DocumentDB.
When you're checking documents, for example, from ID cards or a driver's license, for example, it's personalized, yet there aren't different schemas. The solution helps with having a dynamic and perfect read in order to do document review.
Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads.
Amazon DocumentDB is designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of...
We use Amazon DocumentDB; there are quite a few use cases we have solved with AWS components. The primary use case is that of a data lake, and we use S3 primarily for lake purposes, along with other services such as Lambda, SQS, and SNS. There is use of Amazon DocumentDB, but for a different use case, not the primary data lake use case. Regarding Amazon DocumentDB, I have been working with it for approximately three to three and a half years. One primary reason we chose Amazon DocumentDB on AWS is its ability to handle unstructured data, such as PDFs. There's a significant amount of user manuals and documentation related to operational handbooks that we upload into Amazon DocumentDB, and the primary purpose is to make those easily searchable.
I support my customers with Amazon DocumentDB. Amazon DocumentDB is a nice product when using it for smaller registers about websites or when tabular information is needed. Yesterday, I attended to a customer at the end of my workday. This customer has a concentrated database where invoices, orders, bills, and all registers are concentrated on Amazon DocumentDB.
We use the tool for the middleware product we are developing.
We use it in a few ways. Sometimes it functions as a cache for quick lookups using scans. Other times, DocumentDB serves as a complete backend. For example, we built the entire backend of one of our healthcare applications for Sweden using DocumentDB. We store patient records, medical information... everything runs on DocumentDB.
When you're checking documents, for example, from ID cards or a driver's license, for example, it's personalized, yet there aren't different schemas. The solution helps with having a dynamic and perfect read in order to do document review.