NeoDatis Benchmark on Android

After doing a lot of different testing and trying a lot of different settings I finally decided to do some testing. I had some heap size memory when doing the complete TestIndex test with all of the 10000 records, NeoDatis like to store all of entries in it's internal cache, so I settled with 1000 for now, until I can figure out a way to get around the memory related issues.

Here are the result table:

	Perst	SQLite	DB4O	BerkeleyDB	NeoDatis
Insert	1159	6892	4168	4619	25022
Search	599	9481	18261	3405	18325
Iterate	120	290	4392	2889	11126
Delete	1659	6315	7084	5565	10156

It should be noted that the NeoDatis team releases new versions often, so if you have some problem, it might be fixed in a new version.

TestIndex on Android developer phone1(ADP1) with Berkeley DB

After a long day of testing I got some results on the ADP1. BerkeleyDB does seem to like heap space more than the other database managament systems(DBMS), but it seems to be able to run ok. I think I'll need to think about ways to shrink the memory usage of the different tests.

Well here are the results:

	Perst-ADP1	SQLite-ADP1	DB4O-ADP1	BerkeleyDB- ADP1
insert	21150	600824	88059	113668
search	16176	107514	470561	74417
iterate	11747	6777	90657	62190
delete	37704	562522	155778	215499

TestIndex on Android emulator now also with BerkeleyDB

It's taken a bit longer time than I had expected to get some TestIndex results for BerkeleyDB on Android. A while back I had a running version up and running, but managed somehow to messup the serialization part, so I had to create a new version from scratch that does not use serialization. Instead I used BerkeleyDB's custom TuppleBinding which gives somewhat better performance than serilization. I hope to soon be able to post results using serilization as well, to compare the difference in performance. I will also do some research into the other database management systems that I have tested to see if they have similar optimalizations that can be used.

Results from the test in milliseconds.

	Perst-Emu	SQLite-Emu	DB4O-Emu	BerkeleyDB-Emu
insert	15158	72426	46648	55698
search	12480	100528	290541	37612
iterate	8365	5157	51335	29484
delete	25100	65498	93396	100455

TestIndex with DB4O(part two) on Android developer phone(ADP1)

I finished my ADP1 testing early this morning and here are the results.

Here are the results:

	Perst-ADP1	SQLite-ADP1	DB4O-ADP1
insert	20583	444980	83922
search	15982	103047	471148
iterate	11187	6578	88179
delete	28798	432789	156262

Here we also see that DB4O uses a long time on the search as it did on the Emulator, still don't have a good eplanation for this, I can only speculatate that it has something to do with the way it stores its records. But we allso see that SQLite uses a lot of time on the insert and delete part, which I think has to do with free memory, as my ADP1 still has quite a few application installed.

TestIndex with DB4O(part one) on Android Emulator

When I did my last benchmark on the Android I got a question if I had tried out DB4O on Android, something I had not. So I had to try it out, to see how it was to use on the Android platform and compare it to SQLite and Perst. Using object oriented databases makes it alot easyer to develop applications as you can think "objects" all though out the development process, where you don't have to think about converting the results back into obejcts again. Using DB4O on android worked completely painless, and after some searching I found a compatible version of the TestIndex application for DB4O that I could integrate in the android. Below are the results for the emulator, I hope that i can test it on the ADP1 later today. How did I test ? I ran the test index application several times until I got some stable / reliable results.

Here is a graph of the results on the emulator. 

	Perst-Emulator	SQLite-Emulator	DB4O-Emulator
insert	11465	67420	36980
search	9601	90328	226624
iterate	6578	4504	39405
delete	18408	59998	71463

If we look at the results we see that the only thing that is really standing out is the search on the DB4O, I have no good explanation for this.