Item: MongoDB
Rating: 9
Author: Verified User

Overall Satisfaction with MongoDB

Use Cases and Deployment Scope

My company is a non-profit healthcare delivery institute, and has been conducting a number of data science/advanced analytics projects collaboratively with other healthcare and research organizations. We had an experience with using MongoDB for a recent big data project with a university that stores genomic sequencing data in a non-SQL database, and developed a web-based visualization tool presenting phenotype patterns based on the data.

Pros and Cons

Pros

It is basically a well known and popularly used non-SQL database. It provides great performance, especially when reading big sized document or text (such as sequencing), well-developed functions, and online support.
There are many database developers who are already familiar with MongoDB, like other major non-SQL products. It is easy to hire engineers with reasonable payment.
Since our project was genomics research, we handled tables with numerous rows and large file size. MongoDB was performing well in hard conditions and very stable.

Cons

There is no JOIN and TRANSACTION, so it was required to add those by application developers. It was mandatory for us to do it since we had to merge genomics data in MongoDB with RDBS based clinical data.
MongoDB doesn't provide good data wrangling functionalities, such as parsing JSON or XML.
Data type definition in MongoDB is somewhat different than other databases, and results in some learning curves for our DB and app developers.

Return on Investment

There is little negative impact in using MongoDB in terms of ROI, as it comes with reasonable pricing policies.
In project and workforce management perspective, it is easy to predict the budget since many developers are familiar with MongoDB. We don't need a "special" developer for it, which causes uncertainty of salary for the specialty.
MongoDB runs well with most of operating systems, and that's one aspect that makes the product easy to adopt with minimum expenses.

Alternatives Considered

Cassandra and Hadoop

In the beginning, we considered several products in the market. Since our project was a science and research project, our budget wasn't as big as a commercial project, but still, we wanted the product to be scalable so that we could deal with "smooth transition" from research to commercialization. At the end of the discussion, we choose MongoDB rather than other products like Cassandra, simply because we could hire good developers who had expertise in MongoDB. Our management left that decision to developers and let them choose since they knew what's good for them.

Other Software Used

Cassandra, Hadoop

Likelihood to Renew

There is no "very strong" reason why we will renew it. Our project is a big data project, for which we used MongoDB to load and store genomics sequencing data in it. Once it sets up, it is hard to move to another place, unless there is a serious problem in the system or strong motivation to move. MongoDB is a well developed and already qualified product in the market and quite a safe choice. We will move forward in using it as our project scales up.

Likelihood to Recommend

MongoDB is a well developed, commercialized product. There are other products which can be good choices, but MongoDB is a safe choice since it was already validated in the market by many customers. Which means, for any general purpose, it will fit in to some extent. In our project, the problem was extensibility to larger scaled genomics information that may require big data management functions. MongoDB is excellent when it is for a small project, but it is also well supported as the project and size of data to be managed grow.

MongoDB Feature Ratings

Comments

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MongoDB is a safe choice for genomics research project