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.

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.

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.

We have a massive quantity of data that we need to maintain, and we can't put it in a relational database since we need all of the data and want it to be queried quickly.

We maintain it in non-relational databases such as Microsoft Azure Cosmos DB.

It's not a specific feature that I value, but the scalability of this system is the most impressive aspect.

The UI should be improved since if you provide the option to query directly when signing into the Azure portal, it makes no sense if you have such a poor UI for querying that you can't even feed the reports correctly. 

It should offer a simple user interface for querying Microsoft Azure Cosmos DB.

I have been using Microsoft Azure Cosmos DB for a long time, almost forever.

We are always working with the latest version.

It's fairly stable. I have no complaints about the stability of Microsoft Azure Cosmos DB.

Microsoft Azure Cosmos DB is fully scalable.

Users do not connect to Microsoft Azure Cosmos DB directly. Our APIs connect to Microsoft Azure Cosmos DB and are then used by the front end. 

Estimating the number of users is impossible.

Because our complete setup is in Microsoft, we have access to the most premium Microsoft assistance, available 24 hours a day, seven days a week. We have never had a problem with technical support.

The initial setup is straightforward.

The RU's use case determines our license fees. It fluctuates based on how many RUs we have. It's not a fixed-line.

Because our whole solution was hosted on Azure, this was the default option for us. We didn't look into any other possibilities.

I would recommend this solution to others who are interested in using it.

I would rate Microsoft Azure Cosmos DB a seven 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 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.

Microsoft Azure Cosmos DB can be used for various purposes. The query language used for Cosmos DB is very similar to SQL, which gives it an advantage. It's a globally distributed multi-model database service, meaning it supports multiple data models, including documents, key-value pairs, graphs, and time series data models.

It's highly scalable and supports consistency, security, and multiple security options, such as REST and transit encryption. It also provides automatic support for these options. These are some top-level benefits of using Cosmos DB, making it a highly versatile and useful tool.

The multi-model database is the most valuable feature. 

One thing that concerns me is the cost, especially for smaller workloads. Cosmos DB is a little more expensive than other database services, particularly if you have tight-traffic models. However, it does have a few advantages, such as being a multi-model database. The biggest problem is the learning curve and other database services like RDS. 

Additionally, advanced analytics capabilities like real-time analytics and machine learning are not embedded in Cosmos DB. Vendor lock-in is a big concern. Cosmos DB is a proprietary database service offered by Microsoft that might not be compatible with other databases. 

I have been using this solution for three years. I am using the latest version.

From a stability perspective, it's a pretty robust solution designed to offer high availability and fault tolerance. It provides multiple levels of redundancy and automatic failover to ensure data availability and reliability. 

It is a scalable solution and has built-in backup and recovery capabilities. We developed it for one of our clients with around 20-25 users.

When compared to other cloud platforms like GCP and AWS, I think Microsoft needs to work on its tech support.

There is some learning curve associated with this software. It becomes relatively easy to implement if you have an expert to work with. 

The deployment process and maintenance depend on the size of the product and what you're trying to migrate. Generally, one cloud solution architect and one big data developer with Azure experience should be sufficient.

We could see an ROI. The whole idea of migrating to the cloud was for a better ROI, and we can see that now that the customer has moved to the cloud.

As your data grows, the licensing cost can be expensive.

If your existing infrastructure already uses Microsoft services or is more of a Microsoft-dependent solution, it's best to be on Microsoft Azure cloud. This is because it integrates very well, and there is a smooth integration with other Microsoft products that are already running on our products. 

You can also leverage some of your existing licenses, saving you a lot of costs when you move to the cloud. That's one solution I would suggest for anyone who is moving from on-premise to the cloud. 

Overall, I would rate the solution an eight 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.