IDG Contributor Network: Five core attributes of a streaming data platform

As your data-driven organization considers incorporating new data sources like mobile apps, websites that serve a global audience, or sensor information from the internet of things, technologists will have questions about the required attributes of a streaming data platform.

There are five core attributes that are necessary for the implementation of an integrated streaming platform and allow for both the acquisition of streaming data and the analytics that make streaming applications possible:

Low latency: Streaming data platforms need to match the pace of the data sources that they will acquire data from as part of a stream. One of the keys to streaming data platforms is the ability to match the speed of data acquisition with the requirements of the near real-time analytics needed to disrupt particular business models or markets. The value of real-time streaming analytics diminishes when you have to wait for the data to be landed in a data warehouse or a Hadoop-based data lake architecture. In particular, for location-based services and predictive maintenance applications, the time between when the data is created and landed in a data management environment represents a missed customer opportunity at the least or a stranded multi-million dollar asset critical to your business operations at the most.

Scalable: Streaming data platforms are not just connecting a couple of data sources behind the corporate firewall. Streaming data platforms need to be able to match the projected growth of connected devices and the internet of things. This means that streaming data platforms will need to be able to stream data from a large number of sources — potentially millions or even billions of sources, both internally and externally.