Microsoft Azure Cosmos DB Reviews

I use Microsoft Azure Cosmos DB for data engineering.

Microsoft Azure Cosmos DB is fast, and its performance is good compared to normal SQL DB.

Sometimes, the solution's access request takes time, which should be improved.

I have been using Microsoft Azure Cosmos DB for one year.

Microsoft Azure Cosmos DB is a stable solution.

Microsoft Azure Cosmos DB is a scalable solution. More than 100 users use the solution in our organization.

The solution's initial setup is straightforward.

The solution's deployment time depends on how complex the job is. Learning-wise, it takes a few weeks to get your hands on, and then you can get started from there. The solution was implemented through an in-house team in our organization.

Microsoft Azure Cosmos DB is deployed on-cloud in our organization.

I would recommend Microsoft Azure Cosmos DB to other users.

Overall, I rate Microsoft Azure Cosmos DB a seven out of ten.

Cosmos DB has multiple use cases. For instance, we recently developed a custom application for a customer in India. We used Cosmos DB to store data fetched from the initial front end to reduce access times to the application, which is significant for improving user experience. 

For example, when creating a virtual machine through our custom portal, it is essential to check whether a VM with the same name exists in the same or a different subscription. 

Additionally, we needed to enforce naming conventions and limitations on the number of VMs that can be created within the same network. These conditional parameters were managed using Cosmos DB, allowing the initial provisioning process to validate data and configurations instantly. 

This enables us to inform the user right away if there is a duplication or if the creation adheres to predefined rules, offering suggestions based on the UI. This demonstrates the real-time application and benefits of Cosmos DB.

We use Cosmos DB for its key-value storage capabilities. For structured data, we always use SQL Database.

The low-latency data access provided by Cosmos DB improved application performance.

Application performance improvement depends on what kind of optimization you're looking for. Do you want to improve latency or efficiency? Performance tuning depends on that specific goal.

Here's an example: A customer with an application running in an internal system noticed their outbound data flow and charges increasing every month. They were exporting a lot of data for users in Excel format, which was heavy.

I suggested they export the data in CSV format instead. It's lightweight and users can still open it in Excel. This optimizes data usage and costs without compromising user experience.

Cosmos DB now supports unstructured data. It's a key-value store, so we can send data without worrying about strict structure, data types, and so on. Since it's unstructured, it's lighter than a structured database.

We use Cosmos DB for its key-value storage capabilities, while SQL Database is used for structured data.

There is room for improvement in terms of stability. 

I have been using it for a year. 

In my experience, Cosmos DB is definitely stable. But, for any service or application, I wouldn't give it a perfect score. There's always room for improvement. A perfect score would mean no room for improvement. So, I always consider some buffer for improvement.

I would rate the stability a seven out of ten.

Since it's a managed service, Azure backend handles scalability. From a user's perspective, we don't need to worry about scalability.

Right now I'm dedicated to customers of one of India's largest certificate authorities, Reliance Jio. They have a lot of customers and two dedicated Azure data centers in India. I focus on those two data centers, and I see at least 10 to 15 customers heavily using Cosmos DB there.

From the user's perspective, it's a managed database service, so all scalability is managed in the backend. Users shouldn't worry about scalability itself, but they might need to consider if paid region support is needed or if other regions are available. Otherwise, scalability shouldn't be a concern for them.

But if you're configuring Cosmos DB in a non-Azure solution, you'd have to manage scalability yourself. In that case, you'd have to be more conscious about it.

We have dedicated technical support in India for each Azure service, including Cosmos DB. Since I provide the framework, design, and initial implementation, I'm involved in most calls to ensure everything is deployed as designed. 

But for any issues or troubleshooting, there's dedicated support that gets involved and fixes them. I also stay engaged with the product team.

The product team is very proactive.

Positive

I predominantly work on Microsoft SQL Database, among others. Sometimes, we use Cosmos DB for specific adaptations or APIs within Azure.

We've also assisted some customers in migrating from MongoDB to Cosmos DB.

If you're familiar with it, it's not complex at all. But for someone new, it can be a little tricky.

Cosmos DB itself is a cloud-based solution. However, I'm currently working primarily with a hybrid solution: Azure Stack HCI with software-defined networking for the environment.

We don't directly deploy Cosmos DB itself; it's a service within Azure. We use our DevOps pipeline to deploy the entire environment, which includes the application, database, environment (including the virtual network), and any connected service endpoints. 

Everything gets incorporated into the provisioning source or the DevOps pipeline and then deployed from there. It's a pretty streamlined process for us.

If the cost is affordable and you're looking for a managed service for unstructured data, I would definitely recommend using Cosmos DB from Azure. It also has seamless migration options from MongoDB, MySQL, and others. 

So, a managed service is the best way to go if the cost is affordable.

Overall, I would rate the solution a seven out of ten. 

Microsoft Azure Cosmos DB has helped improve the search result quality of our customers' organization. The customer gave us the feedback that they are able to easily find the data they are looking for. It is very quick. That is the best feedback. They have a large amount of data, and they can find it quickly.

Our customer is very satisfied with it. Our branch does not use it yet. We used it for a customer, and the customer is very satisfied so far.

There are no particular factors that need improvement. There is a little bit of a learning curve with scaling workloads, but it works smoothly.

I am still learning it and have only used it for one application so far. 

No issues have been reported regarding the stability. It is very fast.

There was a little bit of a learning curve with scaling workloads, but overall, it went smoothly.

I have not had any challenges. However, the configuration done in a session at Microsoft Ignite looked complicated. It would be a bit challenging to do the same configuration. 

There is a little bit of a learning curve. The onboarding process for the team took about two weeks.

The only feedback the customer gave us was that it was way cheaper than they expected. 

The customer had a high budget, but it turned out to be a little bit cheaper than what they expected. I am not sure how much they have spent so far, but they are satisfied with the pricing.

I would recommend this product. I would like my organization to develop and explore it further. I would rate Microsoft Azure Cosmos DB an eight out of ten.

We handle JSON data and it is compatible with Microsoft Azure Cosmos DB. 

I have found Microsoft Azure Cosmos DB different from other SQL databases like RDBMS. It is non-SQL and helps to manage and manipulate data from the coding, rather than direct data and complex queries. It is quite flexible and offers a complete concentration on the coding part only. Even if one lacks expertise in complex queries, JSON and Microsoft Azure Cosmos DB are quite compatible with each other and makes the database options more enhanced and easy to operate. The additional SQL features allow you to go to Azure's portal and get the queries solved. 

I have been a devoted Microsoft fan, but Redis DB's memory caching capabilities are really making progress. Even if Cosmos DB is continuously improving and is quite advanced in the field of internal memory optimization, I would still recommend Redis DB to a customer. My dilemma still lies in the price of both solutions. I believe if Redis DB is superior and pricier than Cosmos DB, customers will be reluctant to use Redis DB.  

Memory streaming and various optimizations contribute to higher costs but also increased speed. Currently, there's nothing specific I can pinpoint that needs to be added – I haven't made any purchases yet. However, I am inclined to recommend working with it. 

I have worked with Microsoft Azure Cosmos DB for one year.

It is a stable solution. I rate the stability a nine out of ten.

It is a scalable solution. I rate the scalability a nine out of ten. 

We haven’t faced any issues that would make us contact service support or raise tickets

Positive

The solution's initial setup is easy. The deployment took almost one day. We migrated the services from the CRM system, converted them into JSON, and deployed it. I would rate the initial setup an eight out of ten. 

If a customer needs to store JSON data, and the solution doesn't require complex structure and reporting like BI reports and RDBMS, opting for a NoSQL database could be ideal. NoSQL databases are suitable when data isn't structured in a relational manner and when extensive normalization isn't a priority. For efficiently handling JSON data for UI purposes or other needs, a NoSQL database like Cosmos DB is the way to go.

However, in the NoSQL landscape, various options like Redis DB, CouchDB, MongoDB, and Cosmos DB exist. If a preference leans towards Microsoft technologies, then Cosmos DB becomes a logical choice. Comparing Cosmos DB with alternatives like Redis DB is advisable before making a final decision. Thus, my typical recommendation involves considering these factors.

I would Cosmos DB a nine out of ten.

The company is using Microsoft Azure Cosmos DB for business intelligence information, specifically for demand management.

What I like about Microsoft Azure Cosmos DB is that it's easy to do data ingestion and use the data in different applications. If you talk about business intelligence such as the Power BI tool, it's easy to connect because both are Microsoft products. With Microsoft Azure Cosmos DB, it's easy to connect and do data ingestion.

At the moment, because I'm still new in terms of using Microsoft Azure Cosmos DB, I don't have any feedback regarding areas for improvement in the product. So far, it has met all the expectations and needs of my company.

It would be nice to have more options to ingest the data, for example, more file options or more search options. Currently, you can use JSON, but if there were other file types you can use for data ingestion, that would be nice. This is the additional feature I'd like to see in the next release of Microsoft Azure Cosmos DB.

I've been using Microsoft Azure Cosmos DB for the past six months.

Microsoft Azure Cosmos DB is a stable product.

Microsoft Azure Cosmos DB is a scalable product.

We have a partnership with Microsoft, so the response time of the technical support team for Microsoft Azure Cosmos DB is really good at the moment.

Microsoft Azure Cosmos DB was easy to set up.

I've been using Microsoft Azure Cosmos DB, a cloud DB solution. It's deployed in a cloud environment, on a public cloud with security for ourselves.

My company is a partner of Microsoft and also a reseller.

My advice to people looking into implementing Microsoft Azure Cosmos DB is that it would be good for them to use, specifically if they are looking for a NoSQL database to ingest the data and do data discovery using the data in a BI tool. It's easy to ingest the data and work with the data in Microsoft Azure Cosmos DB and understand that, because it is not a SQL database, which means it's not as structured. You can add data, and then do a data discovery, and use it the best way for you. I would recommend Microsoft Azure Cosmos DB.

My rating for Microsoft Azure Cosmos DB is eight out of ten.

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 are streaming some data from Azure Stream Analytics, which will be stored in Microsoft Azure Cosmos DB. Our application will be taken from Microsoft Azure Cosmos DB.

The solution's most valuable feature is its global distribution. We work globally and currently have Azure operating in fire regions. From a global distribution perspective, Microsoft Azure Cosmos DB is good and easy to handle. Since Microsoft handles the solution's main operation, we don't have many headaches regarding its operation.

The solution’s pricing could be improved.

I have been using Microsoft Azure Cosmos DB for more than 2 years.

Microsoft Azure Cosmos DB is a stable solution.

I got instant technical support from Microsoft during an outage issue.

Positive

We use Terraform scripts for the initial setup of the solution, which doesn't take much time.

We implemented the solution through an in-house team. We select which region to host Microsoft Azure Cosmos DB based on the resource group. We use Terraform scripts in the deployment process. We create a database and a document inside the database.

The solution is pretty good in terms of support, but we have some pricing issues with it. We are currently evaluating MongoDB and Apache Cassandra. Apart from the pricing, we didn't face any issues with the solution. We once faced an outage issue with Microsoft Azure Cosmos DB because some back-end updates from Microsoft changed the settings.

Microsoft Azure Cosmos DB is a cloud-based solution. Based on our experience, the solution is pretty good because we operate in multiple regions. There will be a lot of machines sending IoT data, dashboards, and alarm messages. Customers need to be updated simultaneously, which should not take much time. The solution's processing is pretty good.

I would recommend the solution to other users. The solution's usage is pretty good, but users should be careful about the IO threshold value, which is a little bit high.

Overall, I rate the solution eight and a half 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.