InterSystems encourages the adoption of a flexible, practical approach to application development, rather than strict adherence to one of the prevalent development theories. This paper offers advice based upon our experience. However needs, attitudes, and styles vary; we recommend that each programmer choose the development approach that works best for them. Caché supports a wide range of development methodologies, not just those recommended here.
Because of increasing business and governmental pressures to integrate their operations, the financial services industry is developing a number of standards for data exchange and other common functions. Standards such as XBRL, FpML, MDDL, RIXML, and FIXML are all specialized dialects of XML (Extensible Markup Language). Any financial services application with good support for XML will be able to communicate effectively using one or more of the emerging industry standards.
By now, anybody working in the technology sector will have heard of Cloud computing. But the concept is increasingly being paid attention to outside of IT departments, with growing recognition among boardlevel executives of the potential of this range of innovations. Frequently, senior personnel are hearing stories about how the Cloud helps organizations reduce costs, boost efficiency and expand their operations, so they’ll be excited about what the Cloud can do for them.
Customers who switch to Caché from relational databases report that their average performance is up to 20 time faster, running on the same hardware, with no changes to the application. What is it about Caché that lets applications run so fast?
Experts estimate that 85% of all data exists in unstructured formats – held in e-mails, documents (contracts, memos, clinical notes, legal briefs), social media feeds, etc. Where structured data typically accounts for quantitative facts, the more interesting and potentially more valuable expert opinions and conclusions are often hidden in these unstructured formats. And with massive volumes of text being generated at unprecedented speed, there’s very little chance this information can be made useful without some process of synthesis or automation.
With the maturation and wide acceptance of Java, object-oriented programming has moved to the foreground of the application development landscape. Because of their rich data models and support for productivity-enhancing concepts such as encapsulation, inheritance, and polymorphism, object technologies like Java, C++, and COM, are favored by today's application developers.
InterSystems Caché 2015.1 soars from 6 million to more than 21 million end-user database accesses per second on the Intel® Xeon® processor E7 v2 family compared to Caché 2013.1 on the Intel® Xeon® processor E5 family
Impedance mismatch is a term commonly used to describe the problem of an object-oriented (OO) application housing its data in legacy relational databases (RDBMS). C++ programmers have dealt with it for years, and it is now a familiar problem to Java and other OO programmers.
If the administrators responsible for securing applications had their way, passwords would be long complex strings of random symbols, and users would memorize different passwords for every application they use. But in the real world, few people are capable of such prodigious feats of memory. The typical user can only remember a handful of relatively short passwords.
A benchmark of a real-world application, which loads data into a data warehouse for subsequent analysis, was performed. To conduct the benchmark, one module of the Oracle-based application was replicated in Caché ObjectScript. Only about 40 person-hours of work was required to duplicate the functionality of the original module in Caché.
The European Space Agency (ESA) has chosen InterSystems Caché as the database technology for the AGIS astrometric solution that will be used to analyze the celestial data captured by the Gaia satellite.
The Gaia mission is to create an accurate phase-map of about a billion celestial objects. During the mission, the AGIS solution will iteratively refine the accuracy of Gaia's spatial observations, ultimately achieving accuracies that are on the order of 20 microarcseconds.
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