Performance Optimization Options in Inforiver

Inforiver provides a number of robust performance optimization features for large-scale data management, such as reporting, writebacks, scheduling, and exporting large datasets. These enhancements improve report responsiveness, reduce load times, and enable efficient scaling to millions of records.

This section guides you through all performance options available in Inforiver, helping you understand when and how to apply each, along with associated trade-offs.

1. Reporting Matrix

1.1. Performance mode

Inforiver Reporting Matrix offers a high-efficiency performance mode designed for quicker rendering and improved interactivity, especially beneficial for large and complex reports.

What is the difference between normal mode and performance mode?

In normal mode, all hierarchy levels are loaded at once in the visual so as to provide you with advanced capabilities.

When you choose the performance mode, Inforiver loads a limited set of top ‘n’ hierarchies, with the rest loaded on-demand (like the native Power BI matrix). This significantly improves the performance and efficiency.

When should I use the performance mode?

Normal mode is optimal for most reports. However, you can switch to performance mode in reports where performance is critical. This can include,

• Reports with large datasets with over 100,000 cells.

• Complex reports with multiple row and column hierarchies and time-based hierarchical columns.

• Use cases with multi-level structures that often require native Power BI drill-through functionality.

Key Benefits of Performance mode

• Faster load times even for larger datasets

• Improved navigation in complex reports

• Better responsiveness and interactivity

This is a sample performance gain recorded by us. Your results will vary depending on the number of rows, columns, field types, calculations and more.

Is there a valid reason not to switch to performance mode?

Yes. The performance mode involves some trade-offs. A few of the Inforiver features are not supported in the performance mode. This includes:

• Custom totals/aggregations

• Calculated rows (may or may not work depending on the expand/collapse status of hierarchy)

• Formula measures

• Forecasts

• Goal Seek

This is because, for these features to work, the entire dataset must be loaded at once.

Other limitations

A few menu options and features are not available in the performance mode. They are summarized below:

2. Writeback Matrix

2.1. High-performance scheduler

Our optimized scheduler allows for faster run times when scheduling report subscriptions.

We have made our high-performance mode the default, while the legacy/normal mode has been deprecated. Scheduler jobs now run three times faster than before.

This is particularly beneficial for scheduling reports with large datasets. The accelerated scheduling allows for faster exports or delivery to designated destinations.

2.2. Performance Table Layout

To efficiently analyze extensive hierarchical datasets without compromising on performance, we recommend switching to the Performance Table layout.

It is a streamlined table layout that you can enable for optimal performance when there are no dimensions assigned to columns.

When to use this layout:

• Reports without a need for column-dimension breakdown

• For better performance in reports with large number of hierarchies

Key benefits:

• Faster processing and writebacks

2.3. High Performance Storage

Inforiver supports faster and seamless working with large datasets, up to 1 million records with our new, high-performance storage mode.

This mode transforms the way the data input values are stored, retrieved, and updated. When enabled, you’ll notice improved performance and reduced processing times, especially with larger datasets.

When to enable this option:

• Larger datasets up to 1 million records

• Your report requires many data input measures/columns

Key Benefits:

• Reduced processing time

• Scalable for enterprise-grade data management – works with data up to 1 million records

2.4. Optimized Inforiver and Infobridge writebacks

• Experience faster writebacks with the latest versions: In the 3.5.2 release, we have refactored and optimized payloads so writeback processes complete significantly faster.

• Since the Inforiver Writeback Matrix 4.0 release, Infobridge writebacks are also 3X faster, with improved efficiency and scalability.

• Infobridge writebacks can handle larger datasets of up to 10 million records. For Azure SQL destinations, Infobridge writebacks can handle up to 30 million records.

3. Other tips to improve performance

• Incorporate best practices in data modeling.

• Use Power BI or Inforiver filters to load subsets of data instead of the entire dataset.

• Avoid using nested formulas and cell-level calculations.

• Prefer row/column-level calculations and reusable variables/functions.

4. Summary – Finding the Right Balance

As users, you have the discretion to select the best performance option to enhance your experience with Inforiver. The key is to strike the right balance between performance and the capabilities needed for planning and forecasting.