Amazon DocumentDB is a nice product when used for smaller registers about websites or when tabular information is needed. However, when you need more volume or more registers, it becomes complicated because the performance adjustments and tuning are challenging. It's very complicated because there aren't many parameters to adjust, and query optimization is difficult due to limited options. You only have methods and index creation available. Many customers tell me, 'I don't have another way. I need to change the instance type or add another node.'
VP of Innovation & Technology at Virtual Force
Real User
Top 10
2024-04-18T15:22:08Z
Apr 18, 2024
One possible improvement could be a hybrid database solution, where parts of the application leverage a relational database alongside DocumentDB. If a system were heavily relational in nature, a database like PostgreSQL might be a good fit. However, it depends on the client's specific needs. We might use the document capabilities of DocumentDB for lookups. But, if the application is likely to evolve over time and benefits from full document database functionality, that would influence the choice.
There's a bit of a learning curve at the beginning. However, once you learn the product, you understand it much better and it becomes easier to work with. If you have many instances, many technical components in different regions, for example, one in France, one somewhere else, you don't need to build a YPO VPC. We call pre-work and you can connect with Amazon Document DB in the same instance. If you need to create in other ones, you need to build in the same thing or you need to build a replication of Document DB on it. I'd like them to develop a graphical user interface where I can see how much of the solution I'm using. For example, so I can gauge which queries I need to optimize.
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...
Amazon DocumentDB is a nice product when used for smaller registers about websites or when tabular information is needed. However, when you need more volume or more registers, it becomes complicated because the performance adjustments and tuning are challenging. It's very complicated because there aren't many parameters to adjust, and query optimization is difficult due to limited options. You only have methods and index creation available. Many customers tell me, 'I don't have another way. I need to change the instance type or add another node.'
The technical support could be improved.
One possible improvement could be a hybrid database solution, where parts of the application leverage a relational database alongside DocumentDB. If a system were heavily relational in nature, a database like PostgreSQL might be a good fit. However, it depends on the client's specific needs. We might use the document capabilities of DocumentDB for lookups. But, if the application is likely to evolve over time and benefits from full document database functionality, that would influence the choice.
There's a bit of a learning curve at the beginning. However, once you learn the product, you understand it much better and it becomes easier to work with. If you have many instances, many technical components in different regions, for example, one in France, one somewhere else, you don't need to build a YPO VPC. We call pre-work and you can connect with Amazon Document DB in the same instance. If you need to create in other ones, you need to build in the same thing or you need to build a replication of Document DB on it. I'd like them to develop a graphical user interface where I can see how much of the solution I'm using. For example, so I can gauge which queries I need to optimize.