The entire JSON object's size is assumed to be ~14 MB, creates around 200–210 entries into the database.Create a sample JSON object to perform the WRITE and READ operation.Create a project( Java, Node, or Ruby) where used DBs are PostgreSQL and MySQL.In this section, we would see the benchmarking difference between PostgreSQL and MySQL. ![]() In the next 4 sections, we would discuss a few performance differences that make each database stands out. Such a practical framework defines the system under test, the workload, metrics, and experiments. The good news is that MySQL is continuously improved to reduce the differences in heavy data writes.Ī database benchmark is a reproducible experimental framework for characterizing and comparing the performance (time, memory, or quality) of database systems or algorithms on those systems. These features are critical to enterprise or consumer-scale applications, so using the old engine is not an option. But if using InnoDB (which allows key constraints, transactions), differences are negligible. Unfortunately, it's not readily available in recent versions of MySQL. Using the old MyISAM engine in MySQL makes reading data extremely fast. The recent versions of MySQL and Postgres have slightly erased the performance difference between the two databases. ![]() Previously, Postgres performance was more balanced, i.e., reads were generally slower than MySQL, but then it improved and can now write large amounts of data more efficiently, making concurrency handling better. PostgreSQL, popularly called Postgres, presents itself as the most advanced open-source relational database, plus it's developed to be standards-compliant and feature-rich. MySQL has had a reputation as a fast database for read-heavy workloads, although frequently at the expense of concurrency when mixed with write operations. ![]() After that, we would outline some key differences between MySQL and PostgreSQL. We shall then further explain some basic configurations to improve our MySQL and PostgreSQL databases' performance. In this article, we would discuss workload analysis and the running queries.
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