Find out in this report how the two NoSQL Databases solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Actually, with MongoDB, it's difficult to calculate the return on investment; it's too expensive for our use.
Technical support is very costly for me, accounting for twenty-five to thirty percent of the product cost.
It is provided as a pre-configured box, and scaling is not an option.
CosmoDB is better for auto-scale.
Overall, on a scale of one to ten, I would rate MongoDB an eight; it's mostly because we're still running a monolithic environment on old hardware, so there are some limitations with read-write access.
MongoDB is highly scalable.
The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment.
We have not contracted the security options in our contract because they're too expensive; thus, we implement just encrypted databases and not the security pack.
While solutions for other databases like SQL or PostgreSQL already exist, MongoDB requires additional integrations for developing AI solutions.
We have to pay approximately 2,000 euros per month for MongoDB.
We use the free version of MongoDB, so there are no licensing costs.
It operates as a high-speed data warehouse, which is essential for handling big data.
In ReplicaSet, it's acceptable, but if your workload needs more performance, and you must pass to a Sharding model, it becomes complicated in MongoDB; in Cosmos DB, however, it's simple.
MongoDB has definitely helped us improve our network monitoring and reporting dashboard.
It offers flexibility in schema adaptation, allowing us to change the schema and add new data points.
MongoDB Enterprise Advanced is a comprehensive platform renowned for its scalability, user-friendliness, and high performance, underpinned by its flexible document-based storage and open-source model. JSON compatibility, clustering, and security elevate its standing among professionals.
The platform facilitates efficient data management through developer-friendly tools and a strong aggregation framework. MongoDB’s no-schema requirement, supported by community expertise, underlines its adaptability. While its sharding capabilities and affordably support large data volumes, there are aspects such as security enhancement and enterprise tool integration that need attention. Indexing and query optimization pose challenges, alongside high costs. Improvements in analytics and UI could advance its infrastructure further.
What are the key features of MongoDB Enterprise Advanced?Industries leverage MongoDB Enterprise Advanced for significant roles in data storage within IoT platforms, healthcare apps, public service monitoring, and big data analytics. Companies in logistics and telecommunications find it instrumental for business process management and video content management, benefiting from its seamless integration and unstructured data support.
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