Many companies struggle to choose best integration options while communicating with other systems and data sources, both inside the enterprise and with third parties residing outside. Moreover, with SAP systems in the landscape, it is common practice to leave many of the data and software not being integrated at all, which results in poorer overall automation and missed opportunities for optimisation.
There is no one best option for integrating SAP systems with other applications, including other SAP systems, in the enterprise. It depends on the type of application and its nature. There are most commonly used techniques that proved to be effective. For SAP to SAP systems, it depends on the type of the stack, usually it may be as easy as ALE with IDOC, ABAP connector and RFC calls (ABAP to ABAP), or JCo and RFC (ABAP to Java and Java to ABAP). For SAP to non-SAP, most common is SOAP with web services (structured XML over the web), ALE, REST. As a middleware it is often PI systems, or ABAP Gateway. It is not all, especially with new HANA capabilities. Pretty much all SAP systems can communicate or can be extended with Java, Python or use .NET connectors. In this way we often have not one but a few alternatives and a dilemma of what to choose.
Finding the best option does not always mean the most robust. There are several factors that may influence the choice - they will be primarily investigated with regard to effectiveness, reliability, scalability, as well as financial aspects, skillset available, and finally personal sentiment, or let’s call it other human factors.
Growing complexity of enterprise IT landscape in recent years is mainly due to increased number of diverse points it has to integrate with. It is often becoming a jungle of all sorts of connections and interfaces. And it looks like there is little chance to stop it growing, or at least new demands and processes will overshadow standardisation of current solutions. What are key players in the years to come? We would mainly indicate: mobile solutions, cloud, big data with complex analytics, social media, and BYOD.