We use Cosmos DB as our entire storage database solution for our application. We don't use any other relational database. We have a file that we use for configuration, but we use Cosmos for user data.

We have about 100,000 users a week who visit our website. We have plans to increase usage to four times what we're using now.

In our setup, we rely on Azure Cosmos DB primarily for cloud-native applications that demand global scalability. We use it for connecting web apps and implementing search functionalities.

This is an event-driven solution. Most oil and gas companies have folder source systems, where they cannot scale, but they still want to provide real-time data to their end consumers for various analytical use cases and AI/ML processing; this is where we input raw data into the Azure environment of this solution. Then, eventually, we built the API on top of Microsoft Azure Cosmos DB because it's highly scalable. The solution is a little bit expensive, but the businesses are ready to accept it. 

I like to describe it as a programmer's database. .NET developers, in particular, can design and work with the data easily because it's schema-free. Unlike traditional databases, which are considered rigid with their rules, developers really love Cosmos DB because of its schema-free nature and the freedom it offers.

Cosmos is widely used for web applications. You can also use it for inventory management and IoT solutions... there are a ton of different applications.

Our company uses the solution to develop a certain sort of products for our internal companies. We have some child or franchise companies and are developing software for them. 

We use the solution where transactions display to provide views or reports for the console. We also use the solution for an online learning application or portal. 

We have 20,000 to 30,000 users across multiple products, franchise companies, and customers at the backend. Centralized data is global and accessed from all over the world including India, the US, South America, and Asia. 

We have several new projects with the same backend, so our user volume will definitely increase day by day. 

I used to work for a bank in Turkey and used Microsoft Azure Cosmos DB in the bank for reporting. We used the solution for customer relationship management (CRM) and cost management.

Our current project primarily relies on the file system to handle incoming source tests. Within this setup, we capture both metadata and result data from these tests. We extract metadata information from these files and store it in Azure Cosmos DB and we have several software services in place to facilitate this process.

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.

I use Microsoft Azure Cosmos DB for data engineering.

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

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.

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.

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

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.

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.

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.

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. 

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

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.

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.

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

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 use Microsoft Azure Cosmos DB for some web applications.

We normally use Cosmos DB for data storage.

I use the product for storing information related to our automation.

We provide automated solutions to manufacturing plants. 

My current title is that of a Solution Sales Architect.

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.

We use Microsoft Azure Cosmos DB for faster databases.

In our accounting department, we store data in Azure Cosmos DB. We query and store IO-based data there.

Cosmos DB is a non-relational, NoSQL database. We are a solution provider and we implement this product for our clients. It is used for integrating and managing unstructured data such as videos, pictures, and other big objects that you cannot include in a standard database tablet. It is made for these kinds of activities.

Some of our customers include banks, where together with their main relational database, it provides a place for keeping track of unstructured data. The relational database is used to store the regular data, whereas Cosmos DB stores what is unstructured.

I also use this product for my own purposes.

We have a lot of use cases like for the web API backend where we have most of the processing jobs. It supports mobile, browser, and tablet. We have a single face application that interacts with the users and customers. It's backend and frontend architecture. For middleware, we use Kafka integration. We have PowerBI for reporting. 

We are strict users of Microsoft. We use it to deal with huge amounts of data. It's like Databricks and it's structured. All of the sites we have are stored in Cosmos DB.

We use Microsoft Azure Cosmos DB for storing information from third-party systems in JSON format.

I was using Microsoft Azure Cosmos DB to correct some performance issues or see more about my environment.

Our primary use case for this solution is to call confirmation details booked in Cosmos DB.