It's better to first understand what's the computation difference
between Lucene Indexing and database insertiong.

For Lucene Indexing need to stem all words out, sort them, save them
to disk. And since Lucene is an incremental merge model, saved
documents may need to merge and saved again. There are a lot of CPU
and disk operation for each document, which can take fairly a long
time.

For database insertiong, each record usually just need "appending".
Maybe some fields need to be indexed(database index). But that's
usually b-tree. The CPU and disk is much less intensive.

So each case is different, but you can safely say Lucene is slower
than database.

--
Chris Lu
-------------------------
Instant Scalable Full-Text Search On Any Database/Application
site: http://www.dbsight.net
demo: http://search.dbsight.com
Lucene Database Search in 3 minutes:
http://wiki.dbsight.com/index.php?title=Create_Lucene_Database_Search_in_3_minutes


On 6/14/07, Chew Yee Chuang <[EMAIL PROTECTED]> wrote:
Hi, I'm  a new user to Lucene, and heard that it is a powerful tool for full
text search and I'm planning to use it in my project for data storage
purpose. Before the implementation, I could like to know whether there is
performance issue on Lucene indexing process. I have no doubt on the
retrieving and searching feature in Lucene but the indexing process. I have
tested my current system to insert 1000 records in RDBMS storage it took
about 1 seconds. Thus, if I change my solution to Lucene, can Lucene
indexing process perform faster than RDBMS ? I have go through some of the
article talking about the "MergeFactor" and "MaxMergeDocs" parameter for
fine tune the indexing process, but no comparison between Lucene indexing
process and RDBMS insertion. Thus, hope someone who have experience in
Lucene can provide this information or some article that discuss between
Lucene and RDBMS.



I really appreciate any help in this. Thanks


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