Streaming analytics is the latest thing in Big Data: streaming analytics, simply put, enables organizations to leverage their fast Big Data in real-time, improving operational efficiency and customer satisfaction, while enabling new real-time revenue streams. Alex Woodie takes a look at The Forrester Wave™: Big Data Streaming Analytics Platforms, Q3 2014 and builds a very pertinent commentary on scope and findings- below find a summary of his observations, as detailed in his timely article from Datanami.
Why Read the Full Report?
Our CEO says: “When you drive, do you want to look out on the road through your window shield, or do you want to drive using only your rear-view mirror?”. While traditional analytics is looking at historical data (you know, the rear view), streaming analytics is anything but. More and more industry surveys have shown that the time-to-action is the strongest motivator in Big Data technologies adoption- and that is precisely what streaming analytics facilitates.
Most companies don’t have the tools to navigate all the data from the sources they use. The Internet-of-Things, market data, transactions, mobile, sensors, clickstream, network health, logs of all kinds remain untapped because there’s only a narrow window of opportunity to act upon them before they quickly lose their value. So far, only a handful of companies found ways to address this issue through well-rounded, actual technologies that can empower organizations to lever streaming analytics and fructify their continuous, high-volume, high-diversity flow of data. Datanami discusses the top 7 as presented in the Forrester report and explains SQLstream’s position as a Contender.
The Wider Market for Stream Processing
Woodie takes a closer look at some of the technologies that did not fall within the scope of the Wave report, even if their contributions to the field of stream processing are major.
Amongst them, the most notable is Apache Storm- an open source favorite and known for wildly successful implementations like Twitter, it could not be included in the report for lack of streaming analytics operators. Apache Spark was another, as well as a respectable roster of vendors including visualization software developers, in-memory data grid developers, megavendors that don’t sell standalone streaming analytics tools, or any of the NoSQL and NewSQL vendors that offer some analytic functions atop a fast transactional database.
KEY FINDINGS: Fleeting insights are a huge opportunity for companies; Streaming Analytics is here to stay.