Method of calculating the scores of the DB-Engines Ranking
From the webpage:
The DB-Engines Ranking is a list of database management systems ranked by their current popularity. We measure the popularity of a system by using the following parameters:
- Number of mentions of the system on websites, measured as number of results in search engines queries. At the moment, we use Google and Bing for this measurement. In order to count only relevant results, we are searching for “<system name> database”, e.g. “Oracle database”.
- General interest in the system. For this measurement, we use the frequency of searches in Google Trends.
- Frequency of technical discussions about the system. We use the number of related questions and the number of interested users on the well-known IT-related Q&A sites Stack Overflow and DBA Stack Exchange.
- Number of job offers, in which the system is mentioned.
We use the number of offers on the leading job search engines Indeed and Simply Hired.- Number of profiles in professional networks, in which the system is mentioned. We use the internationally most popular professional network LinkedIn.
We calculate the popularity value of a system by standardizing and averaging of the individual parameters. These mathematical transformations are made in a way so that the distance of the individual systems is preserved. That means, when system A has twice as large a value in the DB-Engines Ranking as system B, then it is twice as popular when averaged over the individual evaluation criteria.
The DB-Engines Ranking does not measure the number of installations of the systems, or their use within IT systems. It can be expected, that an increase of the popularity of a system as measured by the DB-Engines Ranking (e.g. in discussions or job offers) precedes a corresponding broad use of the system by a certain time factor. Because of this, the DB-Engines Ranking can act as an early indicator. (emphasis added in last paragraph)
I mention this ranking explanation for two reasons.
First, it is a remarkably honest statement about how databases are ranked. It is as if the RIAA were to admit their “piracy” estimates are chosen for verbal impact than any relationship to a measurable reality.
Second, it demonstrates that semantics are lurking just behind the numbers of any ranking. True, DB-Engines said some ranking was X, but anyone who relies on that ranking needs to evaluate how it was arrived at.