MongoDB Enterprise Advanced and MongoDB Atlas compete in the database management solutions category. MongoDB Atlas holds an edge due to its cloud capabilities, scalability, and ease of integration.
Features: MongoDB Enterprise Advanced is acknowledged for its developer-friendly environment, powerful aggregations, and JSON storage flexibility. It offers strong security features and is known for its flexibility in storage options. MongoDB Atlas is distinguished by its scalability, seamless cloud integration, and ability to handle semi-structured data. Its cloud-native deployment and flexibility in schema make it a preferred choice for organizations seeking efficient and scalable solutions.
Room for Improvement: MongoDB Enterprise Advanced requires better security integrations and updated documentation. Issues with indexing and handling complex table joins are noted, along with calls for enhanced encryption. MongoDB Atlas could improve its query performance for large datasets and make data manipulation easier. Users desire better scalability, third-party tool integration, and more intuitive user interfaces. Both products face security upgrade demands, and MongoDB Atlas users also request cost reductions.
Ease of Deployment and Customer Service: MongoDB Enterprise Advanced offers diverse deployment options across on-premises, hybrid, and private clouds, providing more flexibility than the primarily cloud-focused MongoDB Atlas. Users of MongoDB Enterprise Advanced generally rely on community resources for support, while MongoDB Atlas users can access technical support at a higher cost for the enterprise version. User feedback is generally positive for both products in terms of self-service capabilities and support when supplied.
Pricing and ROI: MongoDB Enterprise Advanced is considered costly, especially in on-premises setups, though the community edition offers a free option for startups. MongoDB Atlas provides a flexible pay-as-you-go pricing model, proving economical for smaller setups on cloud platforms despite its initially high enterprise pricing. Both solutions show potential for ROI when optimized for their use cases, with MongoDB Atlas appreciated for its cloud efficiencies and responsive usage-based pricing.
Actually, with MongoDB, it's difficult to calculate the return on investment; it's too expensive for our use.
I would say we see value in money and return on investment with MongoDB Enterprise Advanced.
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.
We have received fairly good support whenever we reached out to the technical teams; they were prompt.
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.
In CosmoDB, the scalability is much better than with the MongoDB ReplicaSet models.
MongoDB is highly scalable.
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.
When it comes to OLTP transactions, its performance declines.
The stability of the product is very high.
It's pretty much stable; we have not faced any major challenges or difficulties with MongoDB Enterprise Advanced.
Enhancing capabilities for data pipelines and visualization dashboards.
MongoDB Atlas should support containerization.
While solutions for other databases like SQL or PostgreSQL already exist, MongoDB requires additional integrations for developing AI solutions.
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.
From the AWS standpoint, if robust integration and data warehouse integration specific tools are added in the advanced suite, that would definitely be helpful.
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.
We use the free version of MongoDB, so there are no licensing costs.
We have to pay approximately 2,000 euros per month for MongoDB.
For a small company, the cost of MongoDB Enterprise Advanced is reasonable, but for heavy data usage, we see a little bit of cost pressure but it's acceptable.
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.
It offers flexibility in schema adaptation, allowing us to change the schema and add new data points.
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.
| Product | Market Share (%) |
|---|---|
| MongoDB Atlas | 10.5% |
| MongoDB Enterprise Advanced | 11.1% |
| Other | 78.4% |
| Company Size | Count |
|---|---|
| Small Business | 22 |
| Midsize Enterprise | 10 |
| Large Enterprise | 20 |
| Company Size | Count |
|---|---|
| Small Business | 36 |
| Midsize Enterprise | 13 |
| Large Enterprise | 37 |
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?
What benefits should you consider in a solution like 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.
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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