Microsoft Azure Cosmos DB Reviews

We use different Azure services in the development of our solutions. Some of the services we use are Azure Cognitive Services, ADB2C, and SignalR.

For most of the solutions, we use a mixture of Azure SQL Database and Cosmos DB. We use Cosmos DB when the data size is huge, and we need to scale.

Currently, only two people in my organization are working on this solution: one developer and myself. In the future, I think once the system gets deployed, we will have thousands of users. 

Cosmos DB solves certain problems that relational databases cannot handle. It's a multimodal NoSQL database, and it's very scalable. One of the nice features is the ability to auto-scale, plus Cosmos DB's API is easy to use. 

I hope they improve the service. Before last year, improvements on Cosmos DB were very slow. I didn't see many changes in the functionality.

I have been using this solution for four years.

I would rate the stability as nine out of ten.

It's very scalable and fast.

I had developer support with Microsoft Azure. I faced a problem a few years ago, and they helped me solve it.

Positive

It's very easy to set up Cosmos DB. First, you decide what type of API to use, like SQL, Graph, etc., or if you want support for MongoDB or Cassandra APIs. I usually use SQL API. Once you choose the type of API, you create an account and a database. Then you create containers, and you can easily write queries.

I believe there will be a return on investment because using cloud solutions will remove all capital expenses. Cosmos DB's auto-scaling options minimize the cost. Choosing "pay as you go" services cuts costs especially when users are not using the system.

I hope Microsoft lowers the cost further.

We evaluated MongoDB and Cassandra, 

I would rate this solution as eight out of ten.

The APIs are improving and are easy to use. It is easy to set up a new database, and the auto scalability and support for different models are good features.

We mainly use it for products that are based on graph concepts. We are using it for mobile applications and real-time analytics.

We have scaled it from 400 users to more than 1000 clients. We were able to scale efficiently during COVID-19.

The graphical representation of data is the most valuable feature of the solution. We did not face any glitches.

The support tickets are not cheap.

I have been using the solution since 2017.

I rate the tool’s stability an eight out of ten.

We had around 300,000 users. They were distributed globally. I rate the tool’s scalability a nine out of ten.

The support team is not competent. We end up with the wrong agents sometimes. Sometimes, we must buy support tickets. It is not a good idea to have tickets that cost a lot.

Negative

It is a cloud-only solution.

We have also used MongoDB and SQL Server.

We had some challenges at the beginning because our team did not know how to optimize the tool. They made some expensive applications. However, we were able to cut it down by 95%. Overall, I rate the product an eight out of ten.

I use Cosmos DB for geolocation identification.

If you pass by a market on the street, it sends me your location. My application will then send you a personalized notification about relevant products you can buy at the market.

The best feature is the velocity of making queries. 

I would like to see better documentation for this solution. 

The pricing of the solution should be reduced. 

I have been using Cosmos DB for one year. 

I would rate stability an eight out of ten. 

I would rate scalability a five out of ten. 

I would rate technical support a ten out of ten. 

The initial setup is straightforward. It's very easy to start a function or application with Azure. 

The solution is very expensive. 

I would overall rate the solution an eight out of ten.

Primarily, people do not have a clear understanding of the cloud and cloud services. Customers are a little bit scared about taking their data onto the cloud, and they think and they assume that it is not safe. So we just make them understand that databases or services on the cloud are more secure than on-premises infrastructure.

The performance point can be improved because when we run a search query on our on-premises machine and develop connectivity, a response comes in. But sometimes, the response gets delayed, and it can be due to network latency or something else we are yet to figure out.

Performance and high availability are two features I want to be added in the next release because that is the basic requirement of customers. Mostly, we have customers with the bank and banking institutions, and they want their databases perfectly integrated with the high availability feature.

I have been using Microsoft Azure Cosmos DB for less than a year.

It is a stable product. I would give it an eight out of ten. 

It is a quite scalable product. I give it a nine out of ten. There are more than ten users using this product. 

The initial setup was difficult. I would give it a six or seven out of ten.

The pricing depends on the budget allocated to the client; for some, it can be high, and for some not high. But mostly, when the prices are moderate, they are not very high. I would rate it a seven out of ten.

It's a highly scalable, highly robust, and very user-friendly solution. It is easy to set up; the most important point is that it is on a cloud. The solution is also very easy to deploy. Only some connectivity features need to be developed.

I give it an eight out of ten.

We use the product to input data that doesn't require structuring. 

Microsoft Azure Cosmos DB's most valuable feature is latency. 

The tool's pricing is expensive. 

I have been using the product since November 2021. 

Microsoft Azure Cosmos DB is stable. 

The product is scalable. My company has eight users. 

Microsoft Azure Cosmos DB's tech support is okay. 

Microsoft Azure Cosmos DB's deployment is straightforward. 

Microsoft Azure Cosmos DB's licensing costs are monthly. 

I rate the tool a nine out of ten. 

I work for a retail company that uses Cosmos DB internally for access management. You have a graph with a hierarchal model that goes from owner to manager to assistant manager to employee, etc., and you provide access based on this hierarchy. Our workshop manager uses Cosmos DB to track requests for access and who needs to approve them. 

Employees who want to access specific resources will submit a request, and the application owners will approve it. Within the applications, there are often multiple levels of access. So the owner of those processes or files must authorize access. We have nearly 500 users. The security and access management teams mostly use Cosmos DB. 

The company is considering a switch, but that might take many years. Many others have switched and will continue to switch to other solutions. However, after you've invested a couple of years into it, it becomes more challenging because you need to rewrite many things. 

I don't think Cosmos DB has improved our organization. People are using it, but I'm not sure it's the best solution. For one, it's costly. Also, there are other issues with it. You cannot get all the records simultaneously. You can only get it in chunks of 1,500 maximum.

Cosmos DB is a graph database. I could see the advantages when we implemented it because it didn't have much competition. MongoDB was doing it, but it wasn't a popular solution for graphs, structures, and hierarchy. The only competitor was Neo4j.

I have been using Cosmos DB for nearly a year.

I rate Azure Cosmos DB eight out of 10 for stability if you allocate the necessary resource units. It is based on the concept of a resource unit. There are three settings: auto, manual, and another one I can't remember. You can manually set a limit on what goes to the resource unit during a specified time. or it will automatically send and continuously increase. 

This can create some instability. For example, if I limit my resources to 30,000 RUs, I expect to consume, but if the load is higher, it will fail and continue to fail. I will get an error that says, "Too many requests."

If you set it to "auto," you'll have to pay for it. You can adjust the limit, but it will not automatically do it. It requires someone who can think in terms of RUs, not the other databases we usually use. The person should always think in terms of resource units because you're paying for each resource unit. It isn't simply writing queries and pulling the details from the database. That is a steep learning curve. Many assume Cosmos DB is like any other NoSQL or graph DB. 

Cosmos DB is scalable, but there are some limitations on the amount of data you can hold in this partition. I think the maximum is 50 GB. That is a lot of data, so it is scalable, but there is a limit. It isn't infinite. Only 99 partitions are allowed with 50 GB each, then the maximum amount of data is under 5,000 GB.

However, it isn't simple because you need to define each record. You have to decide which partition the records should go to. Suppose I have 100 GB of similar records and want to put them in one partition. That isn't possible. 

I rate Azure support nine out of 10. They respond quickly and will help you manage costs. However, they mainly give you an overview of the issue, so they'll never have an in-depth idea of what you're doing. They aren't the owners of our product, so they don't know much about it, but they can ask you generally: What are you doing? Are you doing too many updates? How can we reduce the cost? 

They usually make common suggestions, but so few technical people understand Cosmos DB, and they will be costly. 

Positive

I have used multiple NoSQL databases. The most common is Neo4j, but people also use MongoDB, which is a little easier. You have optimization and all those features there.

I rate Cosmos DB nine out of 10 for ease of setup. The setup is easy, but backing Cosmos DB takes a little more work. It isn't difficult, but you have to raise a request to Azure support. It isn't in your control. The documentation is good enough that most application developers can handle it by following the steps in the documents.

We did it in-house. Two developers should be more than enough. One person could do it alone, but it's always good to have an extra person to verify that your actions are correct. After deployment, it doesn't require any maintenance. When you want to make a copy, you submit a request to the support team and within 24 hours. 

We haven't seen a return. You could benefit from this, but few engineers know how to use it correctly, so that's a problem. It depends on the company. I believe only large organizations can afford it. 

You also should be ready to invest in developers because it has a considerable learning curve. In other databases, you have something called "data cutover." You can change the whole concept of your data to make it more efficient. That is not possible in Cosmos DB. It's too big and will take years to change, whereas that might take you only two or three days in other databases.

For example, let's say you are paying a hypothetical amount for a mistake you made. We'll say it's $1,000. After a couple of years, you realize that you will only need to pay $200 after fixing that mistake, but it will require too many changes in multiple places to fix that error. You might need to discard your old solutions entirely, and it takes years to rewrite everything. Cosmos DB isn't going to reduce the number of people. Conversely, it's going to increase problems and create more confusion.

I rate Cosmos DB one out of 10 for affordability. It was expensive. We pay almost $1,000 daily to use it. It doesn't work traditionally — it works on resource units — so it's costly. It's a graph DB, which has advantages and disadvantages. Neo4j and MongoDB do the same thing, so it depends on your environment and costs.

There are also issues with how you design it. You cannot create the traditional way like you would in other databases or graph databases. Typically, you would pay a fixed subscription yearly. With Cosmos DB, you pay monthly based on the source unit. That's what is expensive. 

It's harder to find designers and developers based on that. Many solution architects will set something up using the traditional way of thinking. Once you start using it expensively, it's challenging to change that. You end up with millions of records, so it's impossible to change all of them. 

We are considering changing from Cosmos DB to MongoDB.

I rate Azure Cosmos DB six out of 10. I wouldn't recommend it. I suggest using other products like Neo4j and MongoDB. If you must use it, you should hire an expert who understands how to design the tables, indexing, and partition keys. The setup is effortless, but how will you write the code? It should be predetermined.

I use Microsoft Azure Cosmos DB for some web applications.

The most valuable feature of the solution is that it makes it easy for users to access web applications like Visio while not being complex like AWS at the same time.

The pricing of the solution is an area with certain shortcomings. From an improvement perspective, I wish for the solution to offer users an increased storage capacity at a cheaper price.

I have been using Microsoft Azure Cosmos DB for a few months.

I rate the solution's stability eight to nine out of ten. The solution's stability is good.

It is a scalable solution.

There are almost 1,000 users of the solution in my institution.

The solution is deployed on the cloud.

I think that there was a third-party involvement required during the solution's deployment phase.

Right now, I have opted for the student subscription plan, for which Microsoft charges me around 100 USD. The pricing of the solution depends on the solution's usage.

I recommend the solution to those who plan to use it. It is a cloud-based solution that is easy to deploy, easy to access, and provides users with more features compared to other clouds like AWS and GCP.

I rate the overall solution a nine out of ten.

We normally use Cosmos DB for data storage.

There are a lot of security features that can be integrated with Cosmos DB. The solution is easy to use, and it is also easy to integrate with several things for database use cases.

I would like the speed of transferring data to be improved.

I’ve been using it for two to three years, and I’m working on the latest version.

The solution is stable.

The solution is very scalable. We have more than 1,000 users in our company.

The initial setup is straightforward. We deploy Cosmos DB once or twice a quarter. We have three or four teams handling deployment and maintenance, which is about 38 members.

We implement the solution in-house.

We are receiving an ROI with this solution.

Cost isn’t a big hurdle for us right now. The solution is not costly.

I recommend Microsoft Azure Cosmos DB to anyone who wants to use it. If you are using Azure Stack, it is a good solution to use