I'm currently working on a project that's based on Android. Without getting into many details, the software will run on a custom built device. The hardware will never change and will always be the same. That's a definite plus :)
With that said, this project is requiring us to store loads and loads of data on the device - Upwards of 3m rows in some tables. SQLite handles scanning this many rows just fine for us, the problem comes in when we start doing complex joins to bring back all the related data we need. We've thought about denormalizing the database but are afraid that will push the database outside the realm of usable.
We are looking into using an Object Oriented database, something like db4o or NeoDatis. Our hope is that by storing objects we can get rid of our relations on a row level and store them on the object (just like OOP). The problem is we have not been able to find any performance related benchmarks (at least not recent ones) of these ODBs running and being used on Android.
Does anyone have any experience with OODBs on Android and/or with storing and accessing this large amount of data? If so any advice you could provide would be greatly appreciated.
-- Edit
Here's an example of the problem we're facing. It's not related to our app (my NDA says I can't post anything specific) but this example represents the problem well.
Imagine we're building an application to monitor every vehicle that's driving on the New Jersey Turnpike at any given time. For any given car we need to track the car Make and Model, how many people are in the car and what's the demographic of the people in the car. So basically you end up with data that looks something like -
car
id | color | make_id | in_toll_lane | model_id
make
id | name
model
id | name | make_id
car_person
id | age | sex | is_driver | car_id
toll_lanes
id | cars_in_line |