At its core, Valentina DB is a columnar database, but you can treat it much like a traditional relational database.  With its columnar roots, you’ll find your database operations, especially complex queries against databases with records numbering hundreds of thousands or more, far faster than a relational database – with some operations, it may be only twice as fast. With others, its hundreds or thousands of times faster. This is especially meaningful if you are pulling large data sets for analysis with your custom applications. Valentina DB is a long time favorite with financial service application providers.

About Portland Code Camp

Portland Code Camp and SQL Saturday are combining and coordinating efforts to bring 700–800 regional software development professionals together for the opportunity to immerse themselves in seminars, presentations, group exploration, and networking. Participants will be able to engage in their preferred technology, as well as to sample other options, with a focus on extending information exchange and enhancing the cross pollination of ideas.

Portland Code Camp happens on May 22, 2010 at the University of Portland.

Ruslan and Valentina user Kem Tekinay wanted FindContain ( ) to be a little faster. The Valentina developer team  was able to speed this up by 10 times. Indexed search on table with 7 million rows has gone down from 46 sec to 4.6 sec.

You can get this using

• API – VField.FindContains()
• SQL –  WHERE LOCATE( “what”, fld ) <> 0

It is hard to go more than a single .1 release without some aspect of Valentina DB being optimized for speed.

Since there are implementations of Valentina DB and Valentina Reports that work with every major development environment, this makes it possible to create one set of mail merge templates that can be reused again and again. For example, you can use the same basic project (with very small modifications) to do a mail merge using Runrev, Director, C# or other on the desktop, and use the same project with Valentina Office Server – which in turn generates merge output in html, graphics, text or PDF format.

This can even be done remotely. Using the free Valentina Client for iPhone, build an iPhone app that queries a server that, in turn, takes the iPhone data and performs the merge on the server.

While customers come to Valentina DB from a huge spectrum of development backgrounds and tools (from Adobe Director to C++ to Cocoa Objective C), a large number of customers across the board who work with complex data – financial services and medical data – seem to take a shine to Valentina for producing vertical market applications or services.

Well – there is one fix, and that is to change your development environment. The more you rely either on very portable, non-development specific SQL or utilize the cross-platform, cross-environment native Valentina API, the easier it is to move your front end to another development environment.