For my current project I need a SQL parser that parses Oracle SQL statements. Currently I've been using jsqlparser, which worked well for simple queries. But when specific functions occur (e.g. cast() or (+)) the parser fails.

Can anyone suggest a parser that is fully compliant to Oracle SQL?

Best, Will

Have you considered General SQL Parser? I don't have any experience with it myself but browsing their website it has potential. Personally I have rolled my own built on the parser in Eclipse Data Tools Platform (sorry I can't share, it's proprietary), but now I will have to evaluate the one I linked above because it claims to have more coverage of Oracle SQL than my parser does.

I am currently testing a few different relational database management systems. (MySQL, PostgreSQL, Oracle and Firebird SQL) using a Java application to do so.

I was debating what tests I should run to distinguish the performances of each.

The obvious ones would be insert, select, delete and drop.

I would love to hear your opinions and to make this apply to the question answer format I shall ask for the 5 most appropriate tests to indicate performace differences. In an ideal world I would like to mimic real word use.

Thanks to all who answer.

I think that any of them would probably be fine. However, your configuration of the different databases for what you are trying to do would be different based on your application.

Suggested place to start: look for apps similar to yours. See what they are using, if you can. Then start testing the different databases with similar configurations and see what works for you.

Personally I've used Oracle, MySql, and Postgres over the last 11 years and they've all worked well. It's really all in your configuration, which is where a good DBA comes in handy.

Hello, I'm looking for information about how to age data in a db, generally related to Oracle and Sql Server, but any database would be good. Any examples or books containing examples of how the best techniques would be cool.

Bob

In Oracle, partitioning is a very useful for implementing Information Life-cycle Management, this enables you to manage data partition wise and store recent, most accessed data on quicker storage and older data, most of the times less often accessed on cheaper storage. IF this is what you are trying to do, take a look at partitioning. In 11g: interval partitioning, takes out having to pre configure partitions; partitions are now created on as needed basis and reference partitioning. This is also a performance booster because it is now easier to do partition wise joins using PQ. It also saves space because the redundant key information is now in the partition definition.