Performance metrics

Overview

This section presents the results of performance testing conducted on Bold Reports^® On-Premise Edition, focusing primarily on how the system performs when rendering large reports.

The tests also evaluate how the system behaves under concurrent user load, providing a comprehensive view of both report rendering performance and server-side stability. These results are intended to help you assess Bold Reports^® stability, responsiveness, and scalability in real-world usage scenarios.

Report Rendering Performance in On-Demand Mode

The performance evaluation began with testing how Bold Reports^® handles report rendering in On-Demand Mode, which is designed to optimize responsiveness when working with large datasets.

Enabling On-Demand Mode significantly improves performance by rendering only the visible portion of the data initially, allowing faster access to the first page.

Test Environment Configuration

RAM: 16 GB
Processor: 4 vCPUs
Deployment: Azure Virtual Machine
Report Name, Settings: Flat table report with 10 columns
Property settings: On-Demand (PageCreation → Background)

Performance Results

Records	First Page Time (Standard Mode) (mm:ss:ms)	First Page Time (On-Demand Mode) (mm:ss:ms)	Query Execution Time (Standard Mode) (mm:ss:ms)	Query Execution Time (On-Demand Mode) (mm:ss:ms)
100K	00:11:15	00:03:04	00:01:970	00:00:251
500k	00:36:18	00:02:88	00:03:415	00:03:415
1M	01:17:69	00:10:34	00:05:664	00:00:249
1.5M	01:56:60	00:02:87	00:19:200	00:00:249
1.7M	01:58:16	00:02:87	00:13:156	00:00:266
2M	02:20:66	00:06:56	00:15:197	00:00:255

These results confirm that On-Demand Mode significantly reduces the initial load time, even for reports containing over 2 million records.

Learn more about enabling On-Demand Mode and best practices for large dataset rendering: View Millions of Data - Best Practices
Please refer to the limitations documentation for further details.

General Performance Metrics

The following table outlines the performance metrics of Bold Reports^® during report rendering with various row and column counts. The time taken indicates how long it takes to load the specified number of records.

Representative Performance for Various Data Sizes:

Column Count	Row Count	First Page Time (mm:ss:ms)	Query Execution Time (mm:ss:ms)
10	1K	00:03:29	00:00:895
10	50K	00:03:26	00:00:254
10	100K	00:02:73	00:00:254
10	1M	00:02:58	00:00:246
20	10K	00:03:33	00:00:492
20	200K	00:03:56	00:00:242
20	1M	00:03:64	00:00:238

Note: As you can see, the time taken increases with the row count, particularly for larger datasets (100K or more). This highlights the system’s performance when handling large datasets.

Complete Performance Data Table

If you would like more granular details, the full dataset is shown below.

Column Count	Row Count	Records	Time Taken (mm:ss:ms)	Query Execution Time (mm:ss:ms)
10	1K	1K	00:03:29	00:00:895
10	10K	10K	00:02:94	00:00:234
10	20K	20K	00:02:83	00:00:237
10	50K	50K	00:03:26	00:00:254
10	100K	100K	00:02:73	00:00:254
10	200K	200K	00:03:27	00:00:284
10	300K	300K	00:03:12	00:00:287
10	400K	400K	00:30:30	00:00:287
10	500K	500K	00:04:47	00:00:247
10	1M	1M	00:02:58	00:00:246
20	1K	1K	00:03:00	00:00:240
20	10K	10K	00:03:19	00:00:251
20	20K	20K	00:03:19	00:00:251
20	50K	50K	00:03:89	00:00:249
20	100K	100K	00:03:21	00:00:241
20	200K	200K	00:03:56	00:00:242
20	300K	300K	00:03:06	00:00:246
20	400K	400K	00:03:47	00:00:227
20	500K	500K	00:02:90	00:00:229
20	1M	1M	00:03:64	00:00:238

Concurrent User Load Testing

We simulated 100 concurrent users to test how the system behaves under load. This type of test is essential for understanding how the system handles real-world scenarios where many users are running reports at the same time.

The test was conducted in a Kubernetes environment with the following system configuration:

CPU: 4 virtual CPUs (vCPUs)
Memory: 16 GiB RAM

The goal of this test is to help you understand how Bold Reports^® On-Premise Edition performs under stress, allowing you to assess its stability and speed when multiple users are interacting with reports at once.

Test Setup and Key Parameters

The following table outlines the key parameters used during the performance testing, providing detailed information about the test configuration, including the number of concurrent users, test duration, and the specific settings used to simulate the load.

Property	Value	Explanation
Concurrent Users	100	Total users accessing reports simultaneously
Ramp Up period (seconds)	50	Gradual login of users. For 100 users, 2 users log in every second.
Loop	1	Number of times the test will repeat its process.
Thread Life Time (seconds)	700	Maximum duration of the test; ends after the set time, even if incomplete.
Startup Delay (seconds)	2	Initial delay before the test starts, to handle setup time.
RunTime Controller runtime (seconds)	480	Limits how long the test runs before stopping, applied to child elements.
Flow Control Action Pass Duration (seconds)	3	Regulates the speed of requests sent to the server during the test.

Performance Results

The test results highlight the system’s stability under load:

Test Run	Success Rate
1st Run	100%
2nd Run	99.55%
3rd Run	99.91%

These results indicate that the system consistently performs well, maintaining stability across multiple test iterations.