Using SQLite : Small. Choose Any Three. Jay A. Learn how to maintain localized storage in a single file that requires no configuration Build your own SQLite library or use a precompiled distribution in your application Get a primer on SQL, and learn how to use several language functions and extensions Work with SQLite using a scripting language or a C-based language such as C or Objective-C Understand the basics of database design, and learn how to transfer what you already know to SQLite Take advantage of virtual tables and modules "Complex SQL concepts explained clearly.
Richard Hipp, creator of SQLite.
charles leifer | SQLite: Small. Fast. Reliable. Choose any three.
Chapter 2 Uses of SQLite. Chapter 6 Database Design. The important idea here is that the type is recommended, not required.
Any column can still store any type of data. It is just that some columns, given the choice, will prefer to use one storage class over another. The preferred storage class for a column is called its "affinity". But that term was easy to confuse with "no affinity" and so it was renamed. If numerical data is inserted into a column with TEXT affinity it is converted into text form before being stored.
Hence, the string '3.
As an internal optimization, small floating point values with no fractional component and stored in columns with REAL affinity are written to disk as integers in order to take up less space and are automatically converted back into floating point as the value is read out. This optimization is completely invisible at the SQL level and can only be detected by examining the raw bits of the database file.
A column with affinity BLOB does not prefer one storage class over another and no attempt is made to coerce data from one storage class into another. The affinity of a column is determined by the declared type of the column, according to the following rules in the order shown:. Note that the order of the rules for determining column affinity is important. The following table shows how many common datatype names from more traditional SQL implementations are converted into affinities by the five rules of the previous section. This table shows only a small subset of the datatype names that SQLite will accept.
When an expression is a simple reference to a column of a real table not a VIEW or subquery then the expression has the same affinity as the table column. Parentheses around the column name are ignored.
https://benstorlibam.tk Hence if X and Y. Z are column names, then X and Y. Z are also considered column names and have the affinity of the corresponding columns. Hence even if X and Y.
Using SQLite (2010)
Z are not column names and have no affinity. An expression of the form "CAST expr AS type " has an affinity that is the same as a column with a declared type of " type ". Thus, the affinity for columns of a VIEW or subquery are determined by the expression affinity rules above. Consider an example:. The affinity of the v1.
To make this easier, I wrote a lightweight schema migrations extension for the peewee ORM. This extension will automatically handle creating the temporary table and copying over the data, so all you need to do is tell peewee which columns to drop or rename, etc :. Even if you aren't using an ORM you can still use the migrator library to help with schema changes. Now that I've sung the praises of SQLite and described some ways to work around its limitations, I'd like to describe some scenarios where SQLite would be a bad choice. The main consideration there, I think, is when you have multiple web-servers and need to connect to your database over the network.
Both SQLite and Postgres have their place in the developer's toolkit.
Postgres is a phenomenal database, and I could go on and on about how awesome it is. But this post is about clearing up some misconceptions about SQLite, and hopefully convincing you that it is a great choice for many applications, including web development. In that vein, don't be afraid to give SQLite a try -- I'd be willing to bet it would work very well for you! I was asked on a Reddit discussion to quantify how much traffic a site should receive before it is "too much". This obviously depends on a lot of factors ratio of reads to writes, length of time it takes to perform a write, disk speed, etc.
I will share a quote from the SQLite docs , though:. SQLite usually will work great as the database engine for low to medium traffic websites which is to say, The amount of web traffic that SQLite can handle depends, of course, on how heavily the website uses its database. SQLite has been demonstrated to work with 10 times that amount of traffic. Thanks for taking the time to read this post, if you have any questions or comments, please feel free to leave a comment below.
- Android SQLite Essentials (2014).
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- Manchesters Place in the History of the Physical Sciences 1800-2011.
If you'd like to learn more about the topics mentioned in this post, here are some links which you might find useful:. I'll try that for my 'small' admin type apps and see where I go with this :. Thank you for your article, I was not aware sqlite had so many excellent features. I will certainly consider it for my future applications.