For a products catalogue app on iphone which approach is more efficient? Using sqllite db or directly parsing online from xml without db?
For a products catalogue app on iphone which approach is more efficient? Using sqllite
Share
Sign Up to our social questions and Answers Engine to ask questions, answer people’s questions, and connect with other people.
Login to our social questions & Answers Engine to ask questions answer people’s questions & connect with other people.
Lost your password? Please enter your email address. You will receive a link and will create a new password via email.
Please briefly explain why you feel this question should be reported.
Please briefly explain why you feel this answer should be reported.
Please briefly explain why you feel this user should be reported.
For a products catalogue app on iphone which approach is more efficient? Using sqllite db or directly parsing online from xml without db?
Small amounts of data can be loaded as XML directly into memory. Thus, XML would do just fine. When using a large amount of data, a database would be a better option, but it will decrease speed simply because it needs to read/write the data to storage.
With iPhone apps and other mobile phone apps, the difference between memory and storage tends to be very small. Unfortunately, for an app to understand an XML file, it must load the XML in a DOM model. This will eat up additional memory of about the size of the XML. Thus XML is not suitable for large amounts of data. (Or huge records.)
If you have up to 50 products, the balance is in favor for XML. Over 50 and you’re better off with sqllite.
An added bonus of XML is that you need to explicitly save back to storage to update your changes. With databases, any updates to the data tends to be done directly. Thus, with a database you have a bit more problems undoing any errors. However, with XML your changes will be lost if your application crashes. Personally, I prefer it to only update data explicitly on my command, thus I would prefer XML. (But not for large amounts of data.)