It has given us a chance to explain to people that once the bank made the decision to migrate some processes, applications, and data into the cloud, it was a benefit. It's not only about the change of process and application components. It's also about changing the data ownership and data operation. It went hand to hand, actually, to start training them that there is something beyond Oracle and SQL databases. With Mongo, our team was happy to get a chance to learn something new.

However, once some people learned the solution, we did lose them to someone else. It shows how popular it is not only in our organization but in other places as well. 

It fits well. Data we want to keep represents facts. We've ETL'd from operational systems, so there was no need for relational engines. MongoDB allows us, through replication and sharing, to build a robust platform for keeping data. Even when volume starts to be an issue it is really easy to escalate horizontally and connectors do the rest. 

I thought that choosing javascript as the internal query language might be a mistake, but that was a very good choice. 

The fact is all of our users are happy with the stability and quick response times our solutions have. All of them are based on MongoDB as a persistence engine.

It's super easy to develop a couple of solutions for clients with MongoDB, like a quick web page with no clear data structure that they need to spin up quickly to validate some sort of MDTP.

Working with it extends beyond database skills. Utilizing additional tools such as ML frameworks (e.g., TensorFlow), languages like Python for data analysis, and platforms like Apache Spark for distributed computing can enhance one's capabilities in extracting meaningful insights from data.

MongoDB has helped my organization by being able to handle large amounts of data. Nowadays, if users are using our application all the data we store in our database. If you're trying to receive the information from the database, it's important we are able to retrieve the result as quickly as possible.

Migrating to MongoDB upgrades the IT environment and puts users in the NoSQL environment, which is faster.

I work with Kafka. Kafka is sending a lot of data - millions of records in seconds. It is not easy to just pass it into the SQL Server. Instead, we are sending those drivers to the MongoDB Server, the MongoDB database. it is very fast

One of the biggest benefits is the speed and flexibility of the documents, especially when it comes to modifications. It has definitely helped us to function more efficiently.

I like that this solution helps us to manage our allowed time on the release date or entry, but if you have a conventional application where you have to make a lot of queries with the joints, you have to mix the information of several tables. You cannot go to a non-relational database, you have to go to an Oracle or MariaDB or whatever. But if you have other queries like smaller tables with a lot of resistance, MongoDB will be okay.

It's a complex solution, but MongoDB can deal with many kinds of files — I can send video, pictures, voice data, and files. MongoDB can deal with these types of big data. It can handle a lot of files quickly. Older products like MySQL, cannot deal with files quickly.

We capture more than 30 million records every week in IoT NS. 

MongoDB has been serving us well so far. It is easier to maintain the data with its document-based storage.

MongoDB was very easy to install and maintain. We have managed a lot of mobile apps and hosted them in this environment.

It allows us to have an alternative solution to licensed DB's.