![]() Same test with 4 parallel threads MongoDB: 29.9 s Timing 100k reads from database: MongoDB: 43.3 s SQLite: 19.4 s So if I make 100k queries looking up information, it's probably fastest using SQLite than other databases, which run in their own process. ![]() What? Faster? Yes, because it runs in the process, and doesn't require context change to proceed. One very important factor is that it's also faster than many other databases out there. One of most important features of SQLite is that it's included in Python base libs. When Python ORM is required, I'm using peewee. I'm using SQLite for most of my projects, in production and for hobby. ![]() Recently introduced CTE's are killer feature, since we have a bit of parent/children derived column values, and we keep filling values from the parent into the children, while with CTE this could be evaluated everytime (at some cost, but then less data being filled overall). Now this ignores the fact that the db might be changed and wont get the same results for each thread (I can't get the same transaction number from different threads/procs as I can with PG) but still works for some tasks. SELECT xx FROM yy LIMIT ll OFFSET oo ORDER BY zz - where it spreads on different threads "ll" and "oo". Recently I've had some success with speeding up (up to 4 threads) on scaling reads - e.g. Off course if memory usage becomes a problem, simply switching from :memory: to some kind of temp file per process would do it. This is done, since changes can be made in-memory which might not have to be written back. db from the OS into the memory, work on it, and "copy" it back. It is also cross platform, and is present in many Linux package repos.įrom the less little known things I love is the sqlite backup api. It's the best I've seen, and the developers are very responsive to bug reports and pull requests. Those looking for a GUI to view SQLite databases should check out sqlitebrowser. I also found this StackOverflow answer that explains how to easily change a column name in place. I agree that migrations can be a pain, but thankfully our tables are usually small enough that we can alter tables simply be recreating them. Writing GUI models and views over the database on the Python end of things is very straightforward, once you have your SQLAlchemy models set up. Our core simulator is written in Matlab for historical reasons, and we can communicate data easily using the database. Our application is an engineering simulation application. I also read this article entitled "SQLite As An Application File Format," which was the final straw for me to take the plunge. I decided to use SQLite after realizing I was slowly reimplementing many features of a database. Which you can verify by issuing the following command −įinally, you have SQLite command prompt where you can issue SQLite commands for your exercises.We use SQLite as a file format for our desktop application (based on PySide) using SQLAlchemy. The above procedure will end with SQLite installation on your Mac OS X machine. Step 1 − Go to SQLite download page, and download sqlite-autoconf-*.tar.gz from source code section. Though the latest version of Mac OS X comes pre-installed with SQLite but if you do not have installation available then just follow these following steps − The above command will end with SQLite installation on your Linux machine. Step 1 − Go to SQLite download page and download sqlite-autoconf-*.tar.gz from source code section. Following are the following steps to install SQLite − If you do not see the above result, then it means you do not have SQLite installed on your Linux machine. So you just issue the following command to check if you already have SQLite installed on your machine. Today, almost all the flavours of Linux OS are being shipped with SQLite. Step 4 − Add C:\>sqlite in your PATH environment variable and finally go to the command prompt and issue sqlite3 command, which should display the following result.Įnter SQL statements terminated with a " " Step 3 − Create a folder C:\>sqlite and unzip above two zipped files in this folder, which will give you f, sqlite3.dll and sqlite3.exe files. Step 2 − Download sqlite-shell-win32-*.zip and sqlite-dll-win32-*.zip zipped files. Step 1 − Go to SQLite download page, and download precompiled binaries from Windows section. This chapter will take you through the process of setting up SQLite on Windows, Linux and Mac OS X. SQLite is famous for its great feature zero-configuration, which means no complex setup or administration is needed.
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