Nov. 7, 2013
Cloud and big data technologies are now converging to promise cost-effective delivery of big data services. But is it a perfect marriage? Cloud and big data have different goals: big data aims at added value in terms of new information and knowledge while the cloud targets flexibility and reduced cost. However, they can well help each other by
- encouraging organizations to outsource more and more strategic internal data in the cloud and
- get value out of it (for instance, by integrating with external data) through big data analytics.
Unfortunately, a perfect marriage is yet to come.
The current cloud data management solutions have traded data consistency for scalability and performance, thus requiring tremendous programming effort and expertise to develop data-intensive cloud applications with correct semantics.
Furthermore, they have specialized in different kinds of data (structured, unstructured, documents, graphs), which makes data integration and analysis very hard.
Finally, it is often the case that useful data span multisite clouds or even different clouds that do not interoperate. In this talk, I will review current cloud and big data technologies and discuss these issues.
I will also point out current directions of research, in particular, in the context of the (just starting) CoherentPaaS FP7 ICT project we are engaging in.
Patrick Valduriez (Inria)
