{"id":21827,"date":"2024-07-18T16:47:43","date_gmt":"2024-07-18T23:47:43","guid":{"rendered":"https:\/\/tdengine.com\/?p=21827"},"modified":"2025-03-30T23:05:34","modified_gmt":"2025-03-31T06:05:34","slug":"testing-vertical-scalability","status":"publish","type":"post","link":"https:\/\/tdengine.com\/testing-vertical-scalability\/","title":{"rendered":"Testing TDengine\u2019s Vertical Scalability"},"content":{"rendered":"\n

Scaling vertically (or scaling up) refers to increasing hardware resources on an existing server. Ensuring that database management systems are vertically scalable and can make use of these new resources is not an easy task, requiring a well-designed framework with minimal resource consumption internally. Considering the large datasets typically processed by a time-series database<\/a>, scaling up and scaling out are both essential capabilities.<\/p>\n\n\n\n

To test whether TDengine is vertically scalable, we can construct an environment in which a specific hardware resource is the performance bottleneck of the system, and then gradually add resources to the system to see how performance is affected. In this article, the vertical scalability of TDengine will be tested in terms of CPU and disk resources.<\/p>\n\n\n\n

Scaling Up CPU Cores<\/h2>\n\n\n\n

This test is intended to prove that, in a scenario where memory and disk resources cannot become bottlenecks, there is a direct relationship between the number of cores available to TDengine and the write speed of TDengine.<\/p>\n\n\n\n

Methodology<\/h3>\n\n\n\n

In this test, TDengine 3.3.0.0 was deployed from the official Docker image on Docker Hub<\/a>. A fixed number of cores were bound to the Docker container. The taosBenchmark<\/a> tool was used to write data to TDengine using the smart meters schema described in the official documentation<\/a>. The number of vgroups and write threads were both set to 4 initially, but when testing 5 or more cores, these parameters were increased to 12. This ensures that CPU resources remain the performance bottleneck.<\/p>\n\n\n\n

The test data is described as follows:<\/p>\n\n\n\n