Scalability of ASAM ODS Systems
Recently, a lot of key features were introduced to software solutions in order to address the scalability of an ODS system. We can address the demand for not restricting measurement data management services to solely one department or use case, as it is already state-of-the-art.
While Oracle remains as a single and local gateway for access, it surely owns the performance to manage the measurement meta data and access to the mass data very quickly. Our Avalon ODS Server always featured a parallel instantiation to e.g. channel workload from import processes, users and analysis.
With our Avalon Server Suite 2015 we introduced the Avalon Distributor. Now it is possible for all (or many) users to use an Avalon Gateway to balance the workload on multiple other Avalon ODS Servers. Moreover, you can use the distributors with fallback options, so your whole server infrastructure is save. Thus, ODS offers horizontal and vertical scalability in data management.
Within recent times, data access via web was commonly introduced into ODS. Hence, there is a solution to the main challenge of viewing, browsing, pulling or exporting and sharing the data of any data model. Web platform feature applications, such as the ManateeWeb application and the Manatee Integration Platform, provide data access from anywhere in the world. Additionally, the ASAM Web Services and the HighQSoft Query Language Libraries (HQL) enable developers and engineers to integrate their tools, platforms or analysis into ODS without greater efforts or ODS API know-how.
A rather new aspect to ODS is the integration of automated evaluations. Not only import processes may trigger evaluations to validate the incoming data, but also the ODS server itself to conclude some standard (e.g. fleet) analysis. The engineer himself can cause evaluations, too. The important fact is, that the analysis is brought to the data itself. This is not only a backbone to future big data integration, but also valuable for performance, comparability of results and data redundancy. An approach to analysis is always a solution. Our products Merlin Analysis Server for Java integration and our soon-to-be Matlab support via HQL are part of it.
All those aspects of a solution integration match the state of the art in ODS and have enough performance for most cases within the ASAM ODS domain.
Discussed technologies and approaches are very important for further development towards Big Data with measurement data, as current alternatives (big data homegrown) do not address the requirements of measurement data management properly.
News / Outlook / Visions: Performance and Scalability
by Dr. Ralf Nörenberg, HighQSoft GmbH
Outlook on HighQSoft GmbH activities from May 2015 to May 2016 with focus on big data subjects. Introduction to specific research projects.