Hi Santosh,

We have a similar lucene-db combo here at www.uniprot.org. We have lucene index over our datasets for searching and for database we have simple serialized memory mapped file ("a database" in some sense). Lucene index and database are linked through another memory mapped file that maps docIds to database file offsets. Earlier this database layer was berkleyDB but we changed it to serialized memory mapped file because of unnecessary overhead. This has proved to be very fast for our use case that has indexes of about 100 million entries (in some cases a lot more). This approach is helpful in our use case as we have write-once index/database.

Hope this helps.

- Best
Parit Bansal

On 12/28/2017 06:35 AM, Kumar, Santosh wrote:
Hi Trejkaz, Evert, Riccardo,

Thank you for your inputs. We have an application which we plan to migrate to 
Cloudfoundry and are yet to make a decision on DataBase with the contenders 
being PostgreSQL, MySQL, HANA DB, MongoDB. In the current setup, we use HANA DB 
which already has a fuzzy search query. But, when we migrate to Cloudfoundry we 
might use a different database and to keep fuzzy search DB agnostic, I think it 
would be better to have fuzzy search in Java layer rather than in DB layer.

While looking up for examples of fuzzy search with Lucene, I came across 
examples that demonstrate Lucene with file system predominantly, so was 
wondering if there are any samples on ‘How to use Lucene with DB’ or if the 
Java logic remains same for Filesystem or DB (really sorry I am new to Lucene). 
Any differences or things to consider when the data source are different?

Thank you and Regards,
Santosh
On 28/12/17, 4:01 AM, "Trejkaz" <trej...@trypticon.org> wrote:

     On Thu, Dec 28, 2017 at 1:07 AM, Riccardo Tasso
     <riccardo.ta...@gmail.com> wrote:
     > Hi,
     > I am not aware of any lucene integration with rdbms
Derby has a plugin of some sort. I haven't tried it so I have no idea
     what it actually does, but it looks like it adds table functions which
     you could join to other queries.
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