Microsoft Azure Cosmos DB Reviews

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

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.

We use Microsoft Azure Cosmos DB for faster databases.

The most valuable feature of the solution is that it is scalable with multiple master files. The performance of the solution is also good.

Microsoft Azure Cosmos DB's pricing model is complicated, which people don't understand. So, the pricing model should be improved.

I have been using Microsoft Azure Cosmos DB for five years.

Microsoft Azure Cosmos DB is a stable solution.

Microsoft Azure Cosmos DB is a highly scalable solution, and 15 to 20 people use the solution in my organization.

I rate Microsoft Azure Cosmos DB’s technical support an eight out of ten. They do take some time to get to the root of a problem.

Positive

The initial setup is straightforward and needs a few tools to upload.

We have had an ROI with the solution.

The pricing model of Microsoft Azure Cosmos DB is a bit complex.

We are using Microsoft Azure Cosmos DB as a cloud-based solution. Two admins and one manager are required for the deployment and maintenance of the solution.

New users must keep an eye on its pricing models and configure them properly.

Overall, I rate Microsoft Azure Cosmos DB 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.

At the end of the day, Cosmos DB is a database. It is a wrapper over different APIs.

We use Cosmos DB both internally and with our customers. Our internal use is quite extensive. The usage with our customers depends on whether it is an approved technology within their ecosystem.

Because Cosmos DB uses multiple APIs, it is the go-to database for us internally.

Cosmos DB makes life easier because if we want to use Mongo-type data, or Cassandra-type data, or maybe even just a simple cable storage-type data, then graph, there are multiple ways to do this. With Cosmos DB, we can put together a holistic solution when it comes to Azure security policies, Azure Monitor, and access control.

By design, Microsoft Azure Cosmos DB provides multiple APIs. You have to decide where to write to. Will you write to Excel, Word, PPT, or OneNote? You have to do the homework properly. If there is no tool, then there will be no provision, then there is no database.

I would like to see Cosmos DB introduce a feature that would convert machine language to human-readable queries. For example, if we want to generate a simple diagram that shows the relationship between devices and how frequently have they failed at various locations, we have to consider that the IoT data that is put into Cosmos DB, called byte codes, is not readable to humans. This is a machine language type of data. So when we push that type of data it looks like gibberish, because it is not meant for us, meaning we can't write a normal query. We have been asking for years for them to work with the IoT partner to provide a feature to convert the machine language to readable human queries.

I have been using Microsoft Azure Cosmos DB for three years.

The solution is stable. I would give it a five out of five for reliability.

The architectural decisions will tell you how the scaling will happen. 

Scalability is based on the requirements that are set. Configuration decisions can be implemented pretty fast, so the solution scales well. We are predominantly in the US and India, so it is easy to decide which geographies we need to have and which data we need to synchronize. 

For some of our customers, there are data residency rules like the UAE for example, where patient data must stay within the UAE, making it only one geography. When this is the case, we go for multiple replicas. 

Internally, we have more than 150 developers who use Cosmos DB. Overall, the scalability of the solution is a five out of five.

Product support is pretty good. They have a very good roadmap and the team provides regular patches and regular service updates, and they have a very good release plan.

Microsoft's technical support is good, I rate it a five out of five.

Positive

The initial setup depends on the type of setup you require. You have to design it properly. The architects need to do some homework to ensure the purpose and the requirements are clear. There are many design decisions that must be made first. Once those decisions are made, the initial setup is quite easy. 

Deployment of the solution was completed within a week.

Overall, I would give the solution a four out of five for ease of setup.

The deployment of Cosmos DB was completed internally, we managed it ourselves.

The cost is intricate, the calculator is complex because the cloud is all about counting every penny. It may look like small numbers, $0.001 per GB per day, but when we are talking of terabytes of data per day and the numbers will stack up. One month, we had over 500 terabytes. That's why you need a database expert to design it carefully and spend ample time number crunching. If done properly, the ROI will be good.

I would rate Cosmos DB a four out of five in terms of ROI.

Cosmos DB is expensive compared to any virtual machine based on conventional RDBMS like MySQL or PostgreSQL. The reason it is expensive is that it is scalable, reliable and there is no latency. So while Cosmos DB is considered expensive, what a lot of people miss is that the cost includes reliability, scalability, and responsiveness.

Cost also depends on the number of databases, number of replica locations, synchronization, number of queries per minute, and storage. Every client will have a different usage pattern. 

Overall, I would rate Cosmos DB a three out of five in terms of affordability. It is easy to over-provision, and it is easy to under-provision the solution.

Prior to choosing Microsoft Azure Cosmos DB, we did try other tools extensively. Because we have servers, we tried MongoDB, SQL Server, MySQL, and PostgreSQL. We settled on Cosmos DB internally because we didn't want to go for machines and trojaning. We wanted to adopt a platform as a service.  

Cost also ended up being a driving factor.

Overall, I would rate Microsoft Azure Cosmos DB a 10 out of 10.

My current title is that of a Solution Sales Architect.

The biggest benefit of Microsoft Azure Cosmos DB is the general cloud model that Azure gives you. It provides more flexibility from a cost and data perspective. The solution is reasonable. Microsoft gives the best security solutions with zero trust protection.

With Azure, you can start small and grow as you need.

I provide architect solutions on top of Azure. A couple of features that would help me in architectural solutions would be customizable architecture or customizable documentation, which both Microsoft Azure and Microsoft Teams can provide. I can easily pick and choose a couple of architecture and merge them. This would be a very helpful feature for me in my role.

I have had five years of experience working with Microsoft Azure Cosmos DB.

This solution is stable. I rarely receive concerns from my clients that they are facing any downtime or that some solutions or configurations are not working.

Azure cloud is very much scalable however, you do need to consider your database. If I am scaling the product, the traffic will increase and the database also has to be optimized in that way. 

My application is static, so it can be scaled to infinity, but the same cannot be done with the database. The database needs to be sufficient to get the load directly. I cannot go ahead and directly deploy a database with another skill functionality as I have to do some manual effort with downtime involved.

From a scalability perspective, the key database has to be optimized in a better way that can support auto-scaling architecture or scalability architecture.

The initial setup of Microsoft Azure Cosmos DB is straightforward.

Azure is a pay as you go subscription. Each month you utilize the solution and at the end of the month, based upon your utilization, you will get a report and invoice. It depends on the architecture and the services being used, how they are deployed and what the stories are. It is variable.

My general advice to anyone looking to implement Microsoft Azure would be to start small. When you see your application increase or your traffic increase on site, you can slowly scale. 

I would rate the solution a seven out of 10 overall.

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.

Cosmos is a PaaS, so you don't need to worry about infrastructure and hosting. It has various APIs that allow it to integrate with other solutions. For example, we are using a MongoDB-compatible API for customers, which makes it easier for developers on the team who previously used MongoDB or are accustomed to the old document storage paradigm. 

The API compatibility has room for improvement, particularly integration with MongoDB. You have to connect to a specific flavor of MongoDB. We'd also like a richer query capability in line with the latest Mongo features. That is one thing on our wish list. The current version is good enough for our use case, but it could be improved.

We've been using Cosmos DB for about six to eight months.

Cosmos DB's reliability, performance, and scalability are all good. We can't complain. Azure has management outages, and the management windows that Azure publishes are still too big. They provide a 24 hour period in which maintenance will happen. Smaller, specific windows are easier to manage when you have a production system. Otherwise, it does a good job technically.

The scalability of the Azure platform is a given. It's easy to scale and quickly deploy. The API's richness also helped us. We use Cosmos DB for a public-facing application with upwards of a million users.

I think we have all the scalability that we need, and we like that the system doesn't have outages when it's updating. However, an on-prem version is required for some use cases, and they provide this now. 

Microsoft support is good if you contact a specialist. Getting in touch with the right specialist is crucial for whatever technology you're using on Azure. If you reach the right person, it's a dream, but that can be difficult in some cases can be difficult. You might go through several layers of support before you reach the platform experts.

We haven't used another solution for this particular use case. The product was benchmarked on Azure, so we used Cosmos DB. It wasn't like we were looking at different solutions, and we chose Cosmos.

Setting up the whole landscape took about a week. It doesn't take long. It's a PaaS, so the setup is mostly configuration. It's more like provisioning rather than deployment. You could probably set it up in a day if you wanted to. We set it up with an in-house team. About 15 to 20 people support the solution, but they aren't dedicated to Cosmos DB. They work on lots of things. 

Cosmos DB is a PaaS, so there are no upfront costs for infrastructure. There are only subscriptions you pay for Azure and things like that. But it's a PaaS, so it's a subscription service. The license isn't perpetual, and the cost might seem expensive on its face, but you have to look at the upkeep for infrastructure and what you're saving. 

I rate Cosmos DB eight out of 10. I would recommend it for an appropriate use case. However, you need to be aware of the system's limitations. If you're using the DocumentDB system, it's crucial to plan properly for document structure, etc. You also need to plan for failure to ensure that your system can survive when any node fails. Set up clustering, redundancy, high availability, and so on.

We mostly use it for NoSQL use cases. We use it for web applications, mobile applications, and social applications in the financial sector.

It is deployed on-premises and on the cloud, and we are using its latest version but not the one in the public review.

Its wide support to the ecosystem is valuable. We can use this database with a lot of use cases, and that's one of the reasons why we prefer it. We have a lot of vendors, databases, and use cases, and wherever possible, we are trying to standardize databases. It is also secure.

At this stage, we would like more enterprise support. We use MongoDB a lot, and we're trying to get rid of MongoDB. So, I would like to see more features in the Cosmos DB API for MongoDB space.

I have been using this solution for almost two years.

It is stable. It has 99.999% availability, and it is backed by SLAs.

We have thousands of users.

We use the cloud version and the on-prem version. We have our on-prem database engineering team. For the cloud, we are okay with their support.

We use MongoDB a lot, and we're trying to get rid of MongoDB.

It is easy to install. I tried it in a testing environment, and it was easy. Database experts should be able to do it easily.

For the cloud, we don't pay for the license, but for the on-prem versions, we do pay.

I would rate Microsoft Azure Cosmos DB a nine out of 10.

We have a database stored on Microsoft Azure where we fetch records and validate them against the application data that is displayed. We use it as a backend in an application to store data.

Within our organization, there are around 500 people using this solution.

There's no specific feature of Cosmos. Basically, we try to query the database. Since it's unstructured data, all the related fields are stored as a single JSON. You don't have to go ahead and hit multiple tables, or multiple containers. Instead, you get all of those things, relationally, stored in a nested JSON — in one single container itself. This way, you don't have to go back and forth to different tables. There are pros and cons with this feature, but often it makes things easier for us.

I am impressed with the TTL (time to live feature) of Cosmos. If we need to perform a manual addition to a container, we just need to configure the time to live. And then based on that, it can be deleted.

We should have more freedom to tweak it and make our own queries for non-traditional use-cases.

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

Cosmos should be more stable. Sometimes we fetch more than 60,000 records at a time. When we try to fetch large amounts of data, sometimes it breaks-down, requiring us to rescale it. Overall, performance-wise, it needs to be a little more stable. 

I personally haven't had contact with the technical support. Our solution architects deal with support. 

I wasn't involved in the initial setup. We have a DevOps team that was responsible for handling the installation. We are just leveraging it for developmental purposes.

Cosmos should be cheaper. We actually intend to stop using it in the near future because the price is too high — and because of the stability issues. 

Overall, on a scale from one to ten, I would give this solution a rating of seven. Aside from the scalability issues, we haven't experienced any other issues. 

I would recommend Cosmos. It made our lives a lot easier. There's not a big learning curve in order to understand the structure and how to use it. We were good to go with only one container. Anybody who is new can learn quickly.