Technical Architect at a wholesaler/distributor with 1,001-5,000 employees
Real User
Top 5
Oct 21, 2026
My main use case for Microsoft Azure DocumentDB is for existing applications that use MongoDB APIs, and my team mostly wants Azure-managed services but prefers an open-source orientation and foundations. JSON document storage is the primary data model for us in modern application development, and it is a strategic priority for Microsoft Azure DocumentDB. Those are the main points that I keep focused on. I worked for one of my customers where we were using Microsoft Azure DocumentDB, which mostly required throughputs for retrievals. Most of the data we stored in JSON documents were mostly IoT data, so the retrievals and storing are pretty easy. Regarding my main use case with Microsoft Azure DocumentDB, it is mostly very easy for retrieval and putting them in structured ways inside Microsoft Azure DocumentDB. It would be quite formatted and as easy as it is if we compare it to PostgreSQL.
The biggest use case for my team, as we are a BI team with six data engineering teams, was to connect to Microsoft Azure DocumentDB, get the data in the format that my team's application WebFOCUS will utilize, and read that data while adding coding and reformatting the data according to WebFOCUS standards. This allows us to publish reports so that all stakeholders of our organization, such as Bank of America, Bank of Scotland, and all global banks in the case of Mastercard, can access these reports. The primary source is the data coming through this database, and then WebFOCUS will connect to it, get the data into it, reformat it, and add coding to publish reports in different formats, whether graphical, analog, digital, bar chart, histogram, or pie chart.
My main use case for Microsoft Azure DocumentDB is when we modernize applications that use MongoDB on-premise and move them to Azure using DocumentDB. By doing this migration to Microsoft Azure DocumentDB, we avoid having to maintain servers, we have greater resilience in terms of the database and higher performance, where we can scale infinitely and have very good cost control and management. Microsoft Azure DocumentDB allows us to scale quickly during peak load times, without having to provision the servers to the maximum peak as was done previously with on-premise servers. The migration from MongoDB has not been complicated; it just needs a small adjustment.
Cloud Advisor at Digital Cognitive Consultancy Services LLP
Real User
Top 5
Aug 14, 2026
I usually recommend Microsoft Azure DocumentDB for medium-sized companies with a PC scale of less than 1,000 PCs, so it works pretty well with them. It might be a little bit expensive for smaller companies; the tradeoff is between performance and cost, as a higher performance system can deliver what they want in a few seconds rather than a few minutes, which makes sense.
Microsoft Azure DocumentDB is a scalable, fully managed NoSQL database service designed to handle demanding workloads through a schema-free document data model.It is tailor-made for applications requiring scale and performance, supporting JSON documents with rich querying capabilities. The service integrates easily with Azure's ecosystem, offering automatic indexing and multi-region replication, which may be appealing for businesses focused on global reach and real-time analytics....
My main use case for Microsoft Azure DocumentDB is for existing applications that use MongoDB APIs, and my team mostly wants Azure-managed services but prefers an open-source orientation and foundations. JSON document storage is the primary data model for us in modern application development, and it is a strategic priority for Microsoft Azure DocumentDB. Those are the main points that I keep focused on. I worked for one of my customers where we were using Microsoft Azure DocumentDB, which mostly required throughputs for retrievals. Most of the data we stored in JSON documents were mostly IoT data, so the retrievals and storing are pretty easy. Regarding my main use case with Microsoft Azure DocumentDB, it is mostly very easy for retrieval and putting them in structured ways inside Microsoft Azure DocumentDB. It would be quite formatted and as easy as it is if we compare it to PostgreSQL.
The biggest use case for my team, as we are a BI team with six data engineering teams, was to connect to Microsoft Azure DocumentDB, get the data in the format that my team's application WebFOCUS will utilize, and read that data while adding coding and reformatting the data according to WebFOCUS standards. This allows us to publish reports so that all stakeholders of our organization, such as Bank of America, Bank of Scotland, and all global banks in the case of Mastercard, can access these reports. The primary source is the data coming through this database, and then WebFOCUS will connect to it, get the data into it, reformat it, and add coding to publish reports in different formats, whether graphical, analog, digital, bar chart, histogram, or pie chart.
My main use case for Microsoft Azure DocumentDB is when we modernize applications that use MongoDB on-premise and move them to Azure using DocumentDB. By doing this migration to Microsoft Azure DocumentDB, we avoid having to maintain servers, we have greater resilience in terms of the database and higher performance, where we can scale infinitely and have very good cost control and management. Microsoft Azure DocumentDB allows us to scale quickly during peak load times, without having to provision the servers to the maximum peak as was done previously with on-premise servers. The migration from MongoDB has not been complicated; it just needs a small adjustment.
I usually recommend Microsoft Azure DocumentDB for medium-sized companies with a PC scale of less than 1,000 PCs, so it works pretty well with them. It might be a little bit expensive for smaller companies; the tradeoff is between performance and cost, as a higher performance system can deliver what they want in a few seconds rather than a few minutes, which makes sense.