What's the difference between MySQLdb, mysqlclient and MySQL connector/Python?

There are thee MySQL adapters for Python that are currently maintained:

• mysqlclient – By far the fastest MySQL connector for CPython. Requires the mysql-connector-c C library to work.

• PyMySQL – Pure Python MySQL client. According to the maintainer of both mysqlclient and PyMySQL, you should use PyMySQL if:

  • You can’t use libmysqlclient for some reason.
  • You want to use monkeypatched socket of gevent or eventlet.
  • You wan’t to hack mysql protocol.

• mysql-connector-python – MySQL connector developed by the MySQL group at Oracle, also written entirely in Python. It’s performance appears to be the worst out of the three. Also, due to some licensing issues, you can’t download it from PyPI (but it’s now available through conda).

Benchmarks

According to the following benchmarks, mysqlclient is faster (sometimes > 10x faster) than the pure Python clients.

• Benchmarking MySQL drivers (Python 3.4)
• PyMySQL Evaluation
• Python MySQLdb vs mysql-connector query performance

A lot of options provided by users. Little late to party. But my 2
cents in on with benchmarking for pypy 3.7 version.

Stick to mysqlclient if you want faster access and repetitive access

MySQL Connector/Python: 23.096168518066406 [sec]
mysqlclient: 6.815327882766724 [sec]
PyMySQL: 24.616853952407837 [sec]
MySQL Connector/Python: 22.619106769561768 [sec]
mysqlclient: 6.607790231704712 [sec]
PyMySQL: 24.410773038864136 [sec]

Loop… from previous benchmarking…

def q100k(cur):
    t = time.time()
    for _ in range(100000):
        cur.execute("SELECT 1,2,3,4,5,6")
        res = cur.fetchall()
        assert len(res) == 1
        assert res[0] == (1, 2, 3, 4, 5, 6)
    return time.time() - t

For developers using SQLAlchemy

This question was a good starting point for learning what DBAPIs are available for Python and their tradeoffs. However, the libraries mentioned above are ever-changing, and their performance and issues are not set in stone. Hence, testing the individual dialects and evaluating their performance for yourself would be a good approach.

I have provided below links listing the available DBAPIs. Those links include references to each library’s documentation and a commentary on their features and support.

• For MariaDB: https://docs.sqlalchemy.org/en/14/dialects/mysql.html#module-sqlalchemy.dialects.mysql.base
• PostgreSQL: https://docs.sqlalchemy.org/en/14/dialects/postgresql.html#:~:text=DBAPI%20Support-,%C2%B6,-The%20following%20dialect
• More Database dialects can be found in the side menu here.

To understand what DBAPIs are in general, use this link, as well as reading the above mentioned PEP-249. In addition, the diagram below can help you visualise where DBAPIs belong architecturally.

I haven’t done my own testing to verify, but based on what I’ve read:

MySQLdb, mysqlclient, and PyMySQL are packages that provide a similar API.

If you install the MySQLdb package or the mysqlclient package with pip, then a MySQLdb module will be installed (for example venv/lib/python3.10/site-packages/MySQLdb/). So whether you install the MySQLdb package or the mysqlclient package, you use it by importing MySQLdb: import MySQLdb.

If you install PyMySQL with pip, then a MySQLdb module will not be installed. But PyMySQL includes an install_as_MySQLdb function that can be used to define a MySQLdb module in memory at runtime, that actually references PyMySQL.

So there are a few ways you can use PyMySQL:

1. import pymysql and use pymysql like you would MySQLdb, since it has the same API.
2. Call install_as_MySQLdb and then use import MySQLdb. (This is probably useful if a dependency imports MySQLdb.)
3. import pymysql as MySQLdb.

My impression is that "MySQL Connector/Python" provides a different API.

(Django’s ORM can be used with either of the 2 APIs. That is, it can be used with the MySQLdb/mysqlclient/PyMySQL API, or the "MySQL Connector/Python" API.)