Data visualization and analysis allows you to get the most out of your Big Data. JReport gives you easy ways to visualize the data, analyze and drill down into it, and deliver the results in different formats. With JReport, connecting to NoSQL databases like MongoDB that store Big Data is a snap. Read about how to use JReport for MongoDB reporting using the native MongoDB connector to visualize and analyze data for better business insights.
MongoDB Reporting & Intelligent Push Down Technology:
JReport supports the use of intelligent pushdown technology where queries (aggregation or detailed) from JReport are passed on to the database via data source connectors. The database then performs all the heavy lifting computations and submits the aggregate result sets back to JReport, which are then stored in data structures called in-memory cubes. Other information result sets, such as detailed data, are stored in JReport’s detailed data cache. So now when you build reports and dashboards, the data is pulled from these in-memory data structures resulting in huge performance gains over having to directly access the data source. JReport is capable of connecting to any relational database, cloud data source, or Big Data source in order to populate its in-memory cube and detailed data cache. With MongoDB, JReport achieves this through interfaces like the MongoDB Connector for BI or JReport’s native, customized connector that accesses MongoDB’s Aggregation Framework to retrieve aggregation result sets.
In-Memory Cube and Details Cache
MongoDB Aggregation Framework: MongoDB has an Aggregation Framework which is a means to calculate all the aggregated values without having to use their MapReduce functionality. MapReduce is a complete, powerful algorithm, but it is heavier-weight and more difficult to use, and it is essentially overkill when only retrieving aggregation values.
JReport’s native MongoDB connector speaks directly with MongoDB’s Aggregation Framework API to efficiently pull in the aggregation result sets and populate its in-memory data structures.
Outside of aggregation queries, such as detailed queries, JReport leverages its own UDS (user-defined data source) interface to pass actual MongoDB queries to the MongoDB data source.
Once the in-memory cubes and detailed data caches are created, you can quickly start to create reports and dashboards. You can also use JReport’s Visual Analysis tool to easily transform your business data into rich visualizations by picking your own dimensions and measures, using sliders and filters, and adjusting the dynamics of your visualizations on the fly. Visualizing Big Data has never been easier.
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