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Room for improvement in data handling leads to enhanced cost-effective data management performance
What is our primary use case?
I primarily use Oracle databases, but I work with many other databases such as MongoDB Atlas and several cloud databases. I utilize MongoDB Atlas predominantly for training-level projects in resource grooming and for sub-projects at my office. It is used alongside Oracle and Postgres in these training layers.
What is most valuable?
MongoDB Atlas offers replication, which is cheaper than Oracle RAC, making it appealing to certain industries. It is particularly useful for unstructured and semi-structured data because of its performance in these areas. Sharding and partitioning are supported, though they don't reach the same level as Oracle's capabilities. This cost-effective solution assists organizations in data storage and management.
What needs improvement?
It would be beneficial if MongoDB Atlas could better support OLTP aspects and data frames, as well as enhance its capabilities for data pipelines and visualization dashboards. Furthermore, supporting the medallion architecture could be a valuable addition, and incorporating improved spatial and vector handling for geographical data could make it more competitive. Enhancing vector processing for AI capabilities would also be critical.
What do I think about the stability of the solution?
MongoDB Atlas is effective for unstructured and semi-structured data, but when it comes to OLTP transactions, its performance declines. This is a continuous challenge I face when utilizing MongoDB Atlas.
What do I think about the scalability of the solution?
MongoDB Atlas offers sharding as a scalability feature, although it does not perform as well as Oracle. Partitioning is also available; however, it lacks a multi-tenancy architecture, which affects its scalability in comparison.
How are customer service and support?
Technical support from MongoDB Atlas, which is open source, is satisfactory in most cases. However, when compared to top databases like EDB, Postgres, and Oracle, the features of MongoDB Atlas fall short, resulting in an average rating due to higher-expectation features still lacking in its offerings.
How would you rate customer service and support?
What's my experience with pricing, setup cost, and licensing?
The price of MongoDB Atlas is reasonable, which is why many organizations, including mine, are opting for it.
What other advice do I have?
The overall rating for MongoDB Atlas is around 5.5. To improve, MongoDB should enhance support for demanding graph databases, vector databases, and spatial handling. Additionally, improvements in AI capabilities, particularly vector processing, are imperative. These developments could provide MongoDB Atlas with a competitive edge.
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