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Technology

Software technologies:

  • J2EE;
  • Microsoft.NET;
  • CORBA.


RDBMS:

  • Oracle;
  • Essbase
  • MS SQL Server
  • Sybase ASE
  • Sybase ASA
  • Sybase IQ
  • Informix
  • DB2
  • KDB
  • MySQL
  • PostgreSQL
  • Teradata
  • Ingres.

IMDB:

  • TimesTen
  • EXASolution
  • SAP HANA
  • KDB
  • Microsoft COM+ & xVelocity
  • eXtremeDB
  • JavaDB
  • Terracotta

Programming languages:

  • C++;
  • C#;
  • VB;
  • Q
  • Java;
  • SQL;
  • PL/SQL;
  • TSQL;
  • HTML;
  • DHTML;
  • PHP;
  • ASP;
  • JSP;
  • XML.


CASE tools:

  • ORACLE Designer;
  • Sybase Power Designer;
  • ERWin/BPWin;
  • Rational Rose.


Hardware and software platforms:

  • Sun Sparc (Solaris), HP (Unix), Intel IA-32 (Windows, Linux);
  • Real time: QNX, RTC-Kernel, VxWorks, OSR8.

For years, databases and disk drives have been interdependent. Database systems couldn't keep up with application performance requirements without access to a robust I/O. Relatively cheap memory technology which can run entire databases in memory, has created an impetuous for the creation of various new in-memory databases that share RAM with applications which removes several steps in the process of managing data.

Although in-memory databases are the future of next-generation analytic applications, affordable memory has also created affordable ways to boost the performance of existing databases. SQL applications can get a boost by replacing hard-disk drives with solid-state drives.

In the coming years, IT organizations will need to decide between solving issues with existing database technology or to move to an in-memory database system to deploy their advanced analytic applications. A combination of these two methods is the probable strategy that will be adopted by most organization, however, as lines between databases and application begin to blur, it is evident that databases are moving away from being dependent on hard disk drives. New technology has appeared to address enterprise's needs for more efficient ways to manage, store, retrieve and process big data workloads in all vertical segments.

New technology that expedites big data integration leads to better analysis and quicker business decisions. Utilizing an in-memory database is one method to increasethe processing rate for big data. Real-time applications for various industries such as financials, insurance, telecom can benefit for from an in-memory database.

In-memory databases can be up to 100 times faster than conventional databases, making them a must for the latest big data applications.