What is your primary use case for Microsoft Azure Cosmos DB?

We have a very large team of developers who develop a solution for our customers. In the part where they need some infrastructure on Microsoft Azure, we deploy entire environments of different types such as development, testing, production, and pre-production to Microsoft Azure and configure it, monitoring that infrastructure, one of them being Microsoft Azure Cosmos DB. Later, we hand over those resources to our development team and they can start to use it. For example, we have one application which is for one of our post offices where they host their main application for tracking packages, for sending packages, and for everything they provide to their customers. The main database for this solution is Microsoft Azure Cosmos DB.

My main use cases in my company for Microsoft Azure Cosmos DB are to store data for semi-structured and unstructured data and to retrieve data for data agents.

My main use cases for Microsoft Azure Cosmos DB are usually warehouse software, as I'm mainly using it for storing all our data that has to go in and out very quickly.

My main use cases for Microsoft Azure Cosmos DB involve real-time analysis, where we store information inside Microsoft Azure Cosmos DB as a speed layer, and this use case is now in production. We do analysis with Synapse, and I currently use Microsoft Azure Cosmos DB with a generative application for an agent, serving as the memory cache for the agents. Additionally, we utilize it for user information, such as user settings, and also for microservices applications to store information about products or entities within the customer platform. In our project, we use Microsoft Azure Cosmos DB for all things related to AI. We utilize it as an object store for tool calling for agents, where we store the results of information that the agents call from the MCP server. This capability helps our agents retrieve information and provide context to the workflow, as well as the reasoning of the model for the agents. Furthermore, another implementation of Microsoft Azure Cosmos DB is for the conversational layer of our application, which involves conversation feedbacks and all types of user information, being essential for the context of our agents and our model.

Our main use cases involve syncing client accounting data and containers, and we use it as a read database. We do not put much into it; we just sync from their on-premises data or from other APIs, and we collect things. We have not used enough features of Microsoft Azure Cosmos DB yet, which is why I'm here to try to use more. We're trying to figure out how to do more by linking data from things like documents and our SQL structured databases into Microsoft Azure Cosmos DB. Our goal is aggregating our clients' data to run searches or reporting, and we're trying to learn how to use it more. I evaluate the enterprise-grade security features of Microsoft Azure Cosmos DB in terms of data encryption and access control as excellent.

My primary use case for this solution is collecting compliance data, which we use for SOC 2, SOX, and SOC 1 reporting.

We are in retail and marketing, and Microsoft Azure Cosmos DB gives us the opportunity as a retail industry to store catalog data. This is essentially used for event sourcing. In my department, it is particularly useful for our catalog data storage and marketing operations.

Our current use cases for Microsoft Azure Cosmos DB include IoT-based applications such as home automation, conferencing, and industrial automation, utilizing devices like microphones and speakers.

We built a chatbot for one of the clients, which is a trading-related chatbot that assists with trading queries. We use Microsoft Azure Cosmos DB to store customer interactions.

We use Microsoft Azure Cosmos DB mostly for maintaining our user databases in the document databases. Our firm has an app where each individual user's home screen is personalized according to their preferences, web searches, and metadata. For this, we maintain tags, and those tags, associated with each individual customer's mobile number, are stored in Microsoft Azure Cosmos DB to drive personalization and hyper-personalization on the app's home screen.

Some of the use cases for Microsoft Azure Cosmos DB include storing log files and generating keys for our clients inside Microsoft Azure Cosmos DB. It helps us solve the problem of generating unique identifiers for our clients in Brazil, as we have many clients in our company. The system serves to generate unique keys for client attendance.

Our use case for Microsoft Azure Cosmos DB is storing track and trace data, mainly for regulated markets.

We use Microsoft Azure Cosmos DB emulator to display database contents and occasionally perform manual data edits when necessary. We utilize it for general database emulation tasks.

I have been using Microsoft Azure Cosmos DB for the last five years for IoT-based data saving and other purposes. We use non-structural data for various reasons. For instance, we are using artificial intelligence to save multiple data sets coming from different sources.

I worked on an entity data client project that handled multiple users from digital products, like a Stream player similar to Netflix. It is called Play Plus, with a user base of seven million and a website that attracts eighty-two million unique users per month. We store the data from these users in Cosmos DB to ensure a fast connection between the user profile and the advertising system.

I am using it to store our data. We are using Azure Cosmos DB to store our JSON-based documents.

We use Microsoft Azure Cosmos DB to store document-type data, graph data, and key-value type data. It is a globally distributed database, which we mainly utilize to store document-type JSON data. In my project, I work with core SQL-type queries. Using the API, we are storing JSON data in Microsoft Azure Cosmos DB with a database and container-level architecture. This involves storing items using a partition key for optimized query performance. We get data from BLOB storage. After some processing, we are storing it in the JSON format in Microsoft Azure Cosmos DB.

In our project, I used Microsoft Azure Cosmos DB primarily for storing new or updated JSON documents.

We mainly use Azure Cosmos DB across different projects in our service-based organization. It has been consistently used in projects that require maintaining and creating NoSQL databases. Our team leverages Azure Cosmos DB for these needs.

Our corporate mission is to help companies achieve more with their data, which often means unifying your data. We have a SaaS solution and have built a Copilot with Copilot Studio on top, as well as some of the Azure AI services, which is now Foundry. We are starting to use it to allow people to use natural language to ask questions of their data. We are early in our journey, but I suspect it will work well for us.

We have been using Cosmos DB for everything involving non-relational data. Recently, we’ve been utilizing it more for AI purposes, especially for conversation histories.

We are using Cosmos DB in several different ways. We receive unstructured and semi-structured documents from partners, and we use Cosmos DB to push the data in and scale it to kick off internal processes. We receive notifications from our customers to take action quickly regarding the energy grid. Cosmos DB is also used in a different project for our settlement system, where it is used as a queuing engine for the change notification portion.

Our primary use case is mirroring the data for reporting.

Our primary use case for Cosmos DB is unstructured data. We utilize it to spin up databases quickly.

Our primary use case for Azure Cosmos DB is storing information for our large accounting application, which integrates several sites on SharePoint Online. We use event programming to store all calls in Cosmos DB, so we can redo them and have them persist in the database.

The primary use case is focused on advanced analytics. We use Microsoft Azure Cosmos DB for storing results from OpenAI models, acting as a temporary information repository for APIs, and for log systems. We also experiment with its Vector Search capability.

We utilize the solution for big data, which is collected from IoT devices and streamed through a number of Azure services. The data is then landed in the Cosmos database for analysis later.

We would have the product at the edge, passing it off to another service like Postfix. It was a platform that allowed us to sell a service to customers, enabling certain clients to email us securely. We used it to take everything through email security, which included policies allowing specific emails from certain domains.

Our primary use case is a product to generate insights from several terabytes of data. The main problem was accuracy, as we couldn't get accurate insights because the data was hallucinating. After some trial and error, we found a solution with Azure Cosmos DB and MongoDB and got an acceptable cosine similarity score. We use Azure Cosmos DB collections and Azure functions to get the results we were looking for.

We have numerous healthcare AI use cases, including utilization management, documentation, letter generation, and voice call creation. These are both real-time and non-real-time use cases. My team is the platform team that enables the services. The ML teams are the practitioners who work on these products.

Our primary use case for Azure Cosmos DB is mainly as a Document DB and vector DB.

I am building an extension app for DocuSign. One of the ways for me to demonstrate this is by using a third-party database. I read and write data from Cosmos DB using DocuSign tools.

I'm the primary systems architect at DocuSign. We just launched a product at called Intelligent Agreement Management, and a central pillar of that is schema understanding. We use Microsoft Azure Cosmos DB as our schema store. It's the brains of our entire system.

Our primary use case for Microsoft Azure Cosmos DB is as a solution for customers who are not necessarily migrating an existing application but are looking to build something more cloud-ready and scalable. The objective is to provide a scalable and flexible database solution that does not require the compatibility requirements of Azure SQL, allowing for fast data access across regions without latency concerns. They are not looking for all the compatibility requirements for Azure SQL, but they are looking for something that they can scale quickly without latency.

Our primary use case for Cosmos is the storage of shell-fed signs and our pricing systems. We use it as a transactional database on the back end.

We primarily use Microsoft Azure Cosmos DB as a transactional data store and for some event-driven applications. We utilize the change feed, and the function app triggers quite a bit. MPerks, our customer loyalty application, uses it. It has become our go-to database, and we hardly touch SQL Server for new stuff.

I develop applications. I developed an application where I had to search the Azure Cosmos DB database for values related to suspicious entities. It involved retrieving, sorting, and manually searching data through queries.

We use Cosmos DB in a multifaceted manner, primarily as an operational data store. Additionally, it serves as an analytics and reporting synchronization platform through Synapse Link, Azure's connective data warehousing solution. By connecting directly to Cosmos using the change feed, we project data into our data warehouse and data lake, facilitating both operational functions and analytical reporting needs.

We use Cosmos DB as our primary data store for all the different software services we offer.

The main use case for Microsoft Azure Cosmos DB is as a key-value store where we store all the user data that we have and perform lookups. We use it at a significant scale, with storage of unique data reaching 12 terabytes and handling up to 3 million requests per second.

In my role, I use Microsoft Azure Cosmos DB fairly extensively across various platforms. At ASOS, we utilize it for order processing to record incoming orders and for commercial integration platforms. Overall, we have numerous use cases.

We use it as our main database for our network access control software, and we use it to store all of the information we need to authenticate different devices and users to the networks of our customers. It maintains all of the necessary data for our SaaS product.

My company developed an anti-money laundering compliance platform specifically for the gaming industry. This multitenant platform utilizes Microsoft Azure Cosmos DB as its core operational database. We have a high-throughput, large-volume data ingestion process, with substantial data flowing into our environment. We needed to solve two problems: ultra-high volume, requiring speedy reads and writes of hundreds of gigabytes of data per day, and the ability to distribute our platform geographically. Azure Cosmos DB's geo-replication features and the ability to host and scale our database across multiple regions, keeping data close to our customers, were primary deciding factors.

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.

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.

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.

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

I use Microsoft Azure Cosmos DB for data engineering.

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

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

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.

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

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.

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.

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.

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.

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

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.

My current title is that of a Solution Sales Architect.

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

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

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.

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 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 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 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.