Our first version of SciChart.js was able to draw a million data-points in a browser, and we have only worked to improve our performance since then.
Version 2.1 of SciChart.js (in BETA now) can draw over 10 million datapoints and has even been tested up to 100 million datapoints. That’s more than enough to show the entire history of Bitcoin in a 1-minute chart, or visualise data in the most demanding applications.
There are a lot of legacy native-code applications in Science, Engineering and Finance which need to render millions of data-points from big-data stores, sensors (telemetry, IoT). Even hardware devices like electronic test equipment, process monitoring equipment can have integrated displays which include real-time charts to visualise data. Many legacy applications are moving toward npm / Typescript / React as a UI tech stack.
Big-Data is a trend across industries and the amount of data to visualise is only getting bigger. If the performance of your JS Chart Library is not an issue now, it will be soon. With new tools like SciChart allowing you to visualise bigger datasets, it will become a competitive advantage to be able to visualise and gain valuable insights from the rich data your organisation has collected.
SciChart solves tomorrow’s problems today: visualising large datasets, or dynamic datasets in data-intensive applications.
Note: Other chart libraries were tested internally but not included in the results below, as we are on focussing on the most popular libraries.
We put them head to head in a demanding performance test that stress your CPU & GPU to the max to find out which is the fastest.
These are the test cases:
Below you can find the performance test results in table form. The test case & parameters are on the left, and the results are in FPS (Frames per second). Drawing speed is measured in FPS (Frames per second – Higher is Better), meaning, the average number of redraws per second during the test. An FPS result above 30 is smooth to the eye.
Heatmap colours highlight the winners & losers. On the right, find the Speed Increase of SciChart.js compared to the second fastest JS Chart Library as a percentage.
We’ll draw a conclusion below, but some immediate takeaways from the table above:
SciChart.js is incredibly fast!
More on the performance test results below…
Let’s see the test results in chart form. Click on a chart to view full size!
The bar charts above make it easier to see how SciChart.js (green) is performing vs. the competition. Even with 1 to 10 million data-points, SciChart.js is drawing charts at high refresh rates, meaning that SciChart is able to plot a chart in record time.
Some competing JS charts drop off very quickly. Take a look at the Candlestick chart test for example. All competitors are struggling with only 1,000 candles. At 10,000, they can barely redraw. Only SciChart.js can handle millions of candlesticks – enough to plot the entire history of Bitcoin in a 1-minute timeframe.
Find out More at the link below.