There is a move towards the usage of NoSQL databases that are taking off rapidly. As proof, the MongoDB database is widely chosen by our clients.
This is not surprising as MongoDB can store huge amounts of data with little or no structure. It doesn’t limit the types of data that can be stored in one place. BSON, the format of data storing in MongoDB, allows storing arrays and other complex data types.
Previously, we’ve had the working approach on how to use the pivot table for MongoDB. But we improved it for even smoother and faster connection.
That’s why, in 2.8, we are going to present a special module for it.
Before, you’ve been using our compressor to connect to a database. For more data handling, we changed the technology and provided you with another better & faster option.
In 2.8, we released the custom data source API – a totally new approach of transferring data to Flexmonster. Based on this feature, we’ve prepared a ready-to-use connector for the MongoDB database to set up the configuration with minimum efforts.
When we are talking about MongoDB, we always have large datasets in mind. And working with client-side tools for data visualization means we depend on the available browser’s resources. Such a dependency can limit the performance when it comes to visualizing data in a web-based pivot table.
Let’s clarify how the process of visualizing MongoDB data is streamlined with the new connector.
Firstly, Flexmonster Pivot sends a sequence of queries to the endpoints established on the server.
And here where the magic begins:
In response, the MongoDB connector sends a document schema to Flexmonster. At this moment, the pivot table component gets to know the shape of a document collection – all the fields, their data types, available filters, and aggregations.
As the next step, the connector responds with all the unique members for rows and columns selected to the slice.
Finally, it sends the processed data to the web pivot table. The “processed” means it has already been filtered, aggregated and sorted according to the client’s request.
Meanwhile, the connector communicates with the database and does all the hard work of preparing the data to a format that fits the Flexmonster Pivot requirements.
The entire process lasts seconds. And all you notice is how quickly you can play with your report in realtime.
With the connector, there is no need to load all the raw data into the pivot table and aggregate it on the client side. All the aggregations are handled by the MongoDB connector located on your server.
Plus, we need to give credit to MongoDB with all the powerful features it provides. As an example, the aggregation pipeline is used to process collection’s documents into a set of aggregated results. As follows, you get the fastest reporting experience due to the reduced size of the data sent to the client side.
Besides, based on the aggregation mechanism that MongoDB framework provides, we developed one more notable feature – interval for dates. With its help, you can define what your dates should look like. You can either split them into days, minutes, seconds intervals or show them raw.
To start you need to:
To keep in mind:
! The MongoDB Connector is a sample that was implemented on the base of our custom data source API method. The source is open and you can always add extensions or make some changes that your business report logic needs.
Our developers were driven by the idea to make the connector as flexible and fast for customers as possible. And we hope we managed this.
Now that you know all the ideas behind and the main flow of how the connector works, go ahead with the step-by-step guide.
All the release 2.8 features are shared in our blog post. Let’s dive in!