StreamBase is a high-performance platform for rapidly building and deploying real time streaming analytics applications. It enables professional developers and business users alike to build these applications using a browser-based, low-code, visual interface. Creating an app is as simple as dragging and dropping components onto a canvas and arranging them into a model. The chief advantage of this system is the ease of use it affords, resulting in a reduced time to develop and deploy applications, and ultimately in a faster time to market. Additionally, citizen development is a real possibility for StreamBase, with the potential to enable self-service streaming app creation and reducing time to market even further. StreamBase also provides a variety of deployment options, including several cloud environments such as AWS and Azure, and deployment as a Docker image.
A wide variety of Accelerators for StreamBase are freely available via the TIBCO community. Each one consists of a collection of pre-built components that have been optimised for a particular use case. Examples include financial fraud, case management, and insurance pricing. Notably, a number of accelerators are built to support the Internet of Things (IoT), including the Connected Vehicles Accelerator, and the IoT Drilling Accelerator. Combined with integration with Jaspersoft for embedded BI and analytics, and the option to deploy on the edge, this allows StreamBase to perform well in IoT environments.
Figure 2 – A LiveView Web dashboard
Although StreamBase integrates with several other TIBCO products, its integration with Spotfire, TIBCO’s general analytics platform, is particularly strong. This integration is focused primarily around predictive analytics and machine learning, due to their synergy with streaming analytics. It is enabled by the Artifact Management Server (AMS), a shared environment for storing and managing assets across both StreamBase and Spotfire. These assets primarily consist of predictive models, created in Spotfire or otherwise (for example, via Statistica), that can then be deployed into StreamBase. StreamBase supports models written in Java, Python and R (via TERR), as well as PMML (Predictive Model Markup Language) and SparkML.
TIBCO Live Datamart is another special case. Technically, it is a separate product. However, it is built on top of StreamBase, and adds significantly to its capabilities. Specifically, Live Datamart is an in-memory data warehouse equipped with a continuous query processing engine. This engine drives alerts and user actions, as well as decision rules that can automatically take action under specified conditions. These rules can be authored in either StreamBase itself or in Microsoft Excel and are stored in AMS. Moreover, Live Datamart provides real time, live visualisation of your streaming data that can be accessed and assembled into dashboards via LiveView Web, a thin web client and dashboard builder for Live Datamart.
