Forrester has identified Software AG’s Apama as the leader in a ranking of 11 streaming analytics offerings, saying many enterprises realise that these tools offer an incredible competitive advantage by enabling immediate action to serve fickle customers, fix operational problems, IoT applications, and respond decisively to competitors.
Forrester has issued its The Forrester Wave report on streaming analytics for Q3 2019, available from Software AG, saying: Most business insights pros equate ‘analytics’ and ‘insights’ with the skills they are vested in — traditional, historical, backward-looking analysis.
“Fortunately, that’s changing! Many leading enterprises realize that real-time analytics — the analytics of the present — is an incredible competitive advantage because they can act now to serve fickle customers, fix operational problems, power internet-of-things (IoT) apps, and respond decisively to competitors. That’s what streaming analytics delivers.
Forrester says its research into providers of streaming analytics uncovered a market in which Software AG, IBM, Microsoft, Google, and Tibco Software are leaders; Cloudera, SAS, Amazon Web Services, and Impetus are strong performers; and EsperTech and Alibaba are contenders.
Apama on top
Software AG’s Apama (a component of its Cumulocity IoT cloud software) came out on top with Forrester saying: “Software AG sets the vision for real-time, industrial IoT. Software AG’s Apama is a full-featured streaming analytics platform that is well suited for any and all real-time applications, on-premises, in the cloud, and at the edge. It hails from the high-speed, unforgiving world of financial trading, so it’s fast and it won’t go down. Those properties make Apama an exceptional fit for real-time, industrial IoT applications in manufacturing, supply chain, and field operations, which are also unforgiving, mission-critical environments.”
As a result of these trends Forrester said organisation needing streaming analytics should look for products offering analytic rigour, spike-proof scalability and availability and deployment freedom.
“Enterprises should look for streaming analytics vendors that have both a breadth of built-in real-time analytics and extensibility capabilities to use externally created analytics such as machine learning models… that are fault-tolerant and can scale quickly to handle spikes in data caused by customer, operational, and market activity [and] that can perform real-time analytics with enough time to act on the real-time insights.”
