Fusion Enables Cross-Database Reporting with Izenda Embedded BI

Izenda created our Fusion feature to let users connect to multiple databases without a data warehouse, expanding the capabilities of our real-time analytics platform.

Izenda created our Fusion feature to let users connect to multiple databases without a data warehouse, expanding the capabilities of our real-time analytics platform.

Cross Database Reporting with Izenda Fusion

Companies often store data in multiple data sources. They need the ability for cross-database reporting from their analytics platform to retrieve data from those multiple data sources for use in reports. Fusion’s in-memory data blending engine enables Izenda customers to utilize cross-database reporting. This means that customers can seamlessly join any of the databases we support in a single query.

Use of Fusion includes cross-platform queries for supported vendors:

  • Azure SQL
  • MSSQL
  • MySQL
  • Oracle
  • PostgreSQL

Fusion contains a powerful unified data query expression as the core concept to represent the comprehensive unified logical data model. It hides every complexity from the user when dealing with numerous database-specific techniques, syntax and so on.

Avoid ETL with Fusion

Most companies will resort to ETL processes to consolidate data to one database. With Fusion, this can be accomplished without moving data. ETL is a very powerful tool and still is necessary for many uses cases. But if this method can be avoided, the company removes one step from the analytics process.

Fusion enables end users can create a report using a table from an Oracle database and one from MSSQL without understanding the underlying repositories. Relationships are configured in the model which allow end users to focus on what they need from the data, not on the query syntax.

A query expression tree parses queries into various independent database-specific query nodes as leaf nodes and all in-memory computation into higher nodes. The query expression tree then is analyzed and optimized to enforce the processing efficiency. Finally, it is transformed into a heterogeneous chain of processing. Here, we leverage another well-known data processing pattern, Map Reduce, to maximize the ability of parallel processing. This also throttles the memory consumption.

Connect to multiple databases with Izenda Fusion and create relationships between databases:

  • Databases can be on different machines. Each gets a unique connection string.
  • Different types of databases are allowed. A MySQL database can be fused with a Microsoft SQL database.
  • Leveraging asynchronous querying in tandem with in-memory query tree and map reduce technologies, Izenda enables fast cross-database querying and multi-step calculations.
  • Izenda does not cache data in memory, nor does it copy any data from your database.
  • Connect to and query multiple databases asynchronously, and then aggregate returned data in memory before sending to the client for rendering.

Check out features like Fusion in Izenda’s embedded analytics solution with a free trial.

Leave a Reply