Microsoft Azure Cosmos DB and MongoDB Atlas compete in the database management sector, both excelling as cloud-hosted database solutions. Cosmos DB may have the upper hand due to its seamless integration with Microsoft products, but Atlas's schema-less architecture is appealing for diverse data handling.
Features: Microsoft Azure Cosmos DB is valued for its scalability, support for both structured and unstructured data, and global distribution with low latency. It integrates well within the Microsoft ecosystem and supports multiple APIs, offering robust interoperability. MongoDB Atlas's main strengths are its flexible schema-less architecture and adaptability, enabling ease of handling unstructured data and complex data integrations. Its scalability and NoSQL capabilities strengthen its appeal to organizations with large datasets.
Room for Improvement: Cosmos DB could benefit from improved cost efficiency and simpler pricing models tailored for smaller enterprises. Furthermore, enhancing database joining capabilities and query complexity will strengthen its offering. MongoDB Atlas needs better tools for data migration and integration, specifically for joining multiple data sources. Both solutions can improve technical support and cost management, aiming to enhance user experience and documentation.
Ease of Deployment and Customer Service: Cosmos DB is favored for its ease of deployment within Azure environments, although customer service reviews indicate inconsistent support. MongoDB Atlas offers similar deployment ease, especially on AWS, but relies heavily on third-party support and user communities for assistance. Both platforms recognize the need for better specialized support while delivering solid infrastructures for basic use cases.
Pricing and ROI: Azure Cosmos DB faces criticism for high costs and a complex pricing model but delivers positive ROI when optimally utilized. MongoDB Atlas's pay-as-you-go pricing model is perceived as more cost-effective and manageable, particularly beneficial for smaller companies. With effective implementation, both solutions offer substantial ROI potential.
Getting an MVP of that project would have taken six to eight months, but because we had an active choice of using Azure Cosmos DB and other related cloud-native services of Azure, we were able to get to an MVP stage in a matter of weeks, which is six weeks.
You can react quickly and trim down the specs, memory, RAM, storage size, etc. It can save about 20% of the costs.
When I have done comparisons or cost calculations, I have sometimes personally seen as much as 25% to 30% savings.
Premier Support has deteriorated compared to what it used to be, especially for small to medium-sized customers like ours.
The response was quick.
I would rate customer service and support a nine out of ten.
I have used them sometimes, even recently, and found the feedback to be spot on our needs.
The features of MongoDB Atlas fall short, resulting in an average rating due to higher-expectation features still lacking in its offerings.
For premium support, I would rate the support of MongoDB Atlas a nine.
The system scales up capacity when needed and scales down when not in use, preventing unnecessary expenses.
We like that it can auto-scale to demand, ensuring we only pay for what we use.
We have had no issues with its ability to search through large amounts of data.
It's very much scalable, and I would rate scalability a nine.
MongoDB Atlas offers sharding as a scalability feature, although it does not perform as well as Oracle.
We have multiple availability zones, so nothing goes down.
Azure Cosmos DB would be a good choice if you have to deploy your application in a limited time frame and you want to auto-scale the database across different applications.
I would rate it a ten out of ten in terms of availability and latency.
When it comes to OLTP transactions, its performance declines.
The stability of the product is very high.
We must ensure data security remains the top priority.
You have to monitor the Request Units.
The dashboard could include more detailed RU descriptions, IOPS, and compute metrics.
Enhancing capabilities for data pipelines and visualization dashboards.
MongoDB Atlas should support containerization.
Initially, it seemed like an expensive way to manage a NoSQL data store, but so many improvements that have been made to the platform have made it cost-effective.
Cosmos DB is expensive, and the RU-based pricing model is confusing.
Cosmos DB is great compared to other databases because we can reduce the cost while doing the same things.
For our service, it was around 300 to 600 euros per month, which was acceptable for our customers.
The price of MongoDB Atlas is reasonable, which is why many organizations, including mine, are opting for it.
The most valuable feature of Microsoft Azure Cosmos DB is its real-time analytics capabilities, which allow for turnaround times in milliseconds.
Performance and security are valuable features, particularly when using Cosmos DB for MongoDB emulation and NoSQL.
The performance and scaling capabilities of Cosmos DB are excellent, allowing it to handle large workloads compared to other services such as Azure AI Search.
I find MongoDB Atlas highly scalable and easy to use, with very good support.
It is particularly useful for unstructured and semi-structured data because of its performance in these areas.
The most valuable features of MongoDB Atlas in handling large data volumes include collection size and its NoSQL database capabilities.
Microsoft Azure Cosmos DB is a globally distributed, multi-model database service providing scalability, user-friendliness, and seamless integration, suitable for managing large volumes of structured and unstructured data across diverse applications.
Azure Cosmos DB is renowned for its scalability, stability, and ease of integration, offering robust support for multiple data models and APIs. Its capacity for handling unstructured data efficiently and providing real-time analytics makes it ideal for applications requiring high performance and global distribution. With features like automatic failover and integration with Microsoft products, users benefit from cost optimization and secure data handling. Enhancement opportunities include simplifying queries, improving documentation, and expanding backup and analytics functionalities.
What are the most important features of Microsoft Azure Cosmos DB?Azure Cosmos DB is frequently used in sectors like web, mobile, IoT, and analytics. It supports applications as a key-value store, processes real-time data, and enables global scalability with low-latency access. Its big data management capabilities and integration with Azure services enhance its utility across industries.
MongoDB Atlas stands out with its schemaless architecture, scalability, and user-friendly design. It simplifies data management with automatic scaling and seamless integration, providing dynamic solutions for diverse industries.
MongoDB Atlas offers a cloud-based platform valued for its seamless integration capabilities and high-performance data visualization. It features advanced security options such as encryption and role-based access control alongside flexible data storage and efficient indexing. Users benefit from its robust API support and the ability to manage the platform without an extensive setup process. Feedback suggests improvements are needed in usability, query performance, security options, and third-party tool compatibility. While pricing and support services could be more economical, there is a demand for enhanced real-time monitoring and comprehensive dashboards, as well as advanced containerization and scalability options supporting complex database structures.
What are the key features of MongoDB Atlas?In healthcare and finance, MongoDB Atlas manages payment transactions and facilitates real-time analytics, powering SaaS solutions and storing large volumes of user data. It enhances scalability, performance, and security for cloud hosting, IoT integrations, and Node.js environments, widely favored for its flexibility and capability to support microservices.
We monitor all Database as a Service (DBaaS) reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.