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. DocumentDB shifts the focus from infrastructure management to application development, highlighting its value for developers.
What are the key features of Microsoft Azure DocumentDB?Microsoft Azure DocumentDB is implemented in industries requiring high-throughput workloads and reliable data handling, such as finance, e-commerce, and IoT. By enabling consistent performance and secure data processing, it can meet market demands efficiently. In retail, DocumentDB handles real-time inventory management, while in finance, it supports transaction monitoring, reflecting its versatility across different sectors.
| Author info | Rating | Review Summary |
|---|---|---|
| Cloud Advisor at Digital Cognitive | 4.0 | I recommend Azure DocumentDB for medium companies due to its superior performance, speed, and elastic scaling, improving transactions and queries. Setup is easy, but it is expensive. I'd like columnar indexing and better analytics features. |
| Director for Gross and Transformation at primproa | 4.0 | I found Microsoft Azure DocumentDB straightforward, stable, and easy to use for secure document management, with good scaling and indexing. I want more AI integration for setup and optimized pricing. It offers clear ROI but faces competition from emerging tools. |
| Cloud architect at a tech vendor with 10,001+ employees | 4.0 | I migrated from MongoDB to Azure DocumentDB for cloud modernization, finding it highly compatible, performant, and scalable, leading to a 30% cost saving. It's a stable solution, though documentation could improve. |
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.
The impact of ACID transactions on my operations is that we have seen about 20 to 30% improvement in transactions from moving from PostgreSQL to Microsoft Azure DocumentDB.
The automated indexing of JSON data in Microsoft Azure DocumentDB has improved our query performance by almost 50%.
In Microsoft Azure DocumentDB, the features I find most valuable are its speed and performance.
I use its ACID transactions for data consistency.
One of the most appreciated aspects of Microsoft Azure DocumentDB is the elastic scaling feature. It has significantly helped manage business growth for two customers who have employed it, experiencing a dramatic rise in improvement.
Additionally, the automated indexing of JSON data improves query performance. Despite the cost issue associated with this feature, the advantages in speed and performance cannot be ignored.
To make Microsoft Azure DocumentDB closer to 10, I would like to see a columnar index as an additional feature.
I would also like to improve the analytics aspect of Microsoft Azure DocumentDB because it does not provide a lot of analytics; if that were available, it would be useful.
From a marketing perspective, one thing competitors could learn is the importance of incorporating a columnar index, as that would really help us.
I have been dealing with the tool for about three years now.
So far, I have not seen any issues with Microsoft Azure DocumentDB, although there are some issues with the SDK as REST APIs sometimes return an error, but I think that is more because of Azure than Microsoft Azure DocumentDB.
The elastic scaling feature in Microsoft Azure DocumentDB has helped manage business growth for two customers who have employed it, and they found a dramatic rise in improvement, but the cost is a big issue.
It is a bit expensive, especially concerning the elastic scale.
I used to work with Azure Database for PostgreSQL previously.
I switched purely because of performance.
The initial setup for Microsoft Azure DocumentDB is pretty straightforward.
It usually takes a few minutes.
If Microsoft Azure DocumentDB does not fit the budget, I would recommend PostgreSQL as the ultimate solution, but it does not really work as much as Microsoft Azure DocumentDB does; Microsoft Azure DocumentDB is very performant and does the work we want at a much lower cost, though elastic scale is the challenge.
We switched a few years ago because one of our customers recommended it, and we tried it out; we found it is working far better from a performance perspective.
About 80% of our customers have shifted to Microsoft Azure DocumentDB, while some are still using Azure Database for PostgreSQL.
I would not say that Microsoft Azure DocumentDB is the best option on the market now, but it is a choice for medium enterprises.
We have not integrated Microsoft Azure DocumentDB with Azure Analytics services, but that is a plan.
I have not done an assessment of the multi-region replication feature for maintaining high availability.
I would rate this review as an 8.
The use cases that we were using for Microsoft Azure DocumentDB were driven by our client, who had a lot of artifacts that they were using because they were a financial institution. They wanted to make sure that they had a good repository where they would be able to track, check in their documents, check out in a more secure manner and put this as a part of their contracting. We had to use this as part of that project as a use case.
The most beneficial features of Microsoft Azure DocumentDB that I noticed is that it appeared to be straightforward. It was ease of use; it was not complicated compared to some of the other tools that are out there. The teams were familiar with it, and it integrated well with other Microsoft products.
The automated indexing of JSON data in Microsoft Azure DocumentDB was helpful for query performance in my case. It helped ensure that we were able to retrieve the document, especially when searching. There was faster retrieval, especially when searching for a document and linking with other documents. That is how I found it quite useful.
Some of these things are seamless with Microsoft Azure DocumentDB's multi-region replication, so you might not really see the impact. It depends on how it is configured; if it is configured well, you might not recognize that the data is replicated at certain intervals for continuity. I have not been able to see the back-end, but I think we could see insights from our dataset. It is seamless, and sometimes you might not recognize what has happened or is happening in terms of availability, which is the beauty of the solution.
Regarding Microsoft Azure DocumentDB's elastic scaling feature, when you do projections of where you sit as a business, especially in financial services, it really helps us to plan for customer growth and transaction growth as well. I found that feature to be quite useful because at least you are not constrained around scaling your business.
For me using Microsoft Azure DocumentDB, there are no immediate areas for improvement right now, but perhaps it would be beneficial to have more integration, especially with Copilot and other AI models, just to make sure that it becomes easy to set up because sometimes you almost have to have technical knowledge in terms of setup and support. I would want to see more AI immersion in setup, monitoring, and support.
Regarding the price of Microsoft Azure DocumentDB, what I have seen is reasonable, given the value. However, what we also want to see is bundling of value because sometimes Microsoft tends to put tiers, and some of those tiers might not necessarily be aligned with current needs. Perhaps that is something they might want to look at in comparison to what we are seeing elsewhere. The value points are there, and we just want to optimize the pricing versus what we are getting.
I have about two decades of experience in this domain, not only with Microsoft tools but with other tools as well.
The solution is still okay; it is still fine, indicating that it is stable and reliable.
Regarding Microsoft Azure DocumentDB's elastic scaling feature, when you do projections of where you sit as a business, especially in financial services, it really helps us to plan for customer growth and transaction growth as well. I found that feature to be quite useful because at least you are not constrained around scaling your business.
The support team was helpful from a response and support point of view. I have not had issues regarding the SLAs that we would have agreed on and the response time, especially when escalating things; I have not had issues with the response times.
I used to work with operating systems like CentOS, Ubuntu, and Linux, but not anymore.
I am currently using ChatGPT cloud and the Codex model. What I am actually doing now is using it to talk to my other solutions like Microsoft in terms of automating my workflows. It is easier because I do not have to think about sitting down and creating something. I just tell it what I want to do, and it does it. I am experimenting and moving forward as we go.
I would estimate about two years of experience with Microsoft Azure DocumentDB setup, though it was on and off.
Microsoft Azure DocumentDB actually feels more familiar in the sense that it was part of the ecosystem that was already being used by the client in terms of Microsoft. At the same time, it was ease of deployment and I think it was quite intuitive for the teams to be able to adopt it and also have this flexibility to scale it and build on top of that.
For me, because in my own business, the return on investment is clear with Microsoft Azure DocumentDB because it supports my daily usage. It is seamless; it embeds within what I want to do. However, with the proliferation of the other tools that are coming up, I think we will probably start to question the value more and more. Microsoft needs to provide more for the value of the dollar you are getting. That is the pressure that is coming everywhere.
Microsoft gives you the base functionality which you can grow from, but some tools perhaps go a bit further because that is their only focus or niche. Microsoft has a bigger portfolio, which is where it becomes a challenge. However, what I have seen with Microsoft is that most of the base functionalities are there, so it is probably just the twenty or thirty percent that might not be there. There is always a trade-off because being part of the Microsoft ecosystem comes with some limitations.
Microsoft tools, especially in terms of databases like Azure SQL, Postgres, or Cosmos DB, are still important databases as part of our ecosystem. The only key issue is perhaps the use cases that we are employing them for that matter now. All of them are useful, but to me, the question is what are you building with either Microsoft or some other database.
I had experience with Microsoft Azure DocumentDB in the past and at the beginning of this year, but right now I am experimenting because of AI. For automation, what is happening now is that I have moved into AI in terms of automating my tasks. This allows me to streamline processes more efficiently. I am exploring Microsoft Power Automate's features and potential uses.
I worked on the side of a partner, where we were supporting deployment for a wider program that was for a client. With Microsoft Azure Analytics, especially from the cloud perspective, you are able to bring insights because most of what we have been looking at is the deployment of cloud solutions. I think it helped us bring insights from huge datasets that we would not ordinarily have been able to access. That is the power I saw, especially concerning data lakes that you would be looking at. That is something I found very useful, particularly in terms of the agile business models that we have; that is where I found the biggest value in terms of the analytics and insights that come out of it.
Regarding support, it is mostly about improving the user experience and just being more proactive and agile. My overall rating of the solution is an eight out of ten, where ten is the best.
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 would highlight the very high compatibility with MongoDB, the high performance, the flexibility it offers, and the security as the best features offered by Microsoft Azure DocumentDB.
In fact, the software has been kept exactly as it was, almost 100% with no specific functionality that I found especially useful or any process that was simplified thanks to the compatibility with MongoDB.
Performing backups and restores with Microsoft Azure DocumentDB is very convenient.
Microsoft Azure DocumentDB has positively impacted my organization by allowing us to reduce database costs by 30%. I achieved that saving due to the scalability possibilities, which allow us not to have the maximum peak provisioned, but to always have it at the minimum necessary computing needs, scaling according to the load that the application is receiving.
I think perhaps in some aspects the documentation could be better, as well as the integration with Azure Backup to improve Microsoft Azure DocumentDB.
I have been using Microsoft Azure DocumentDB for about four years.
I consider Microsoft Azure DocumentDB a stable solution.
Microsoft Azure DocumentDB has responded well to my organization's growth needs in terms of scalability.
My experience with customer support for Microsoft Azure DocumentDB has been fine; I have not had any relevant experience with support.
I was previously using MongoDB before Microsoft Azure DocumentDB, and we decided to change because we wanted to migrate to the cloud that application which was on-premise.
I would advise others considering using Microsoft Azure DocumentDB that they consider it a good alternative to MongoDB.
I have seen a return on investment with Microsoft Azure DocumentDB, specifically a 30% saving in database costs.
My experience with the pricing, implementation cost, and licensing of Microsoft Azure DocumentDB is good overall.
I would rate this product an 8 out of 10.
