Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale. And FlinkCEP is the Complex Event Processing (CEP) library implemented on top of Flink. Users can detect event patterns in streams of events.
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TIBCO BusinessEvents
Score 6.3 out of 10
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Enterprises are surrounded by hundreds of thousands of events that occur continuously. Hidden amongst them can be stalled business processes, opportunities for value creation, potential fraud, dissatisfied customers, failing equipment, and more. TIBCO BusinessEvents® proactively identifies these critical events, responds intelligently in real-time to navigate the fast-moving business environments and optimize outcomes. Decision-making in businesses requires a comprehensive…
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TIBCO BusinessEvents
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Apache Flink
TIBCO BusinessEvents
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Community Pulse
Apache Flink
TIBCO BusinessEvents
Features
Apache Flink
TIBCO BusinessEvents
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
In well-suited scenarios, I would recommend using Apache Flink when you need to perform real-time analytics on streaming data, such as monitoring user activities, analyzing IoT device data, or processing financial transactions in real-time. It is also a good choice in scenarios where fault tolerance and consistency are crucial. I would not recommend it for simple batch processing pipelines or for teams that aren't experienced, as it might be overkill, and the steep learning curve may not justify the investment.
TIBCO BusinessEvents is part of the CEP (Complex Event Processing) family, this means that it fits perfectly in all those scenarios where a correlation between incoming events is required. Where a stateful process is necessary. It does not fit well for a kind of Process Orchestrator scope, where simple events are coming in, and there is a well-defined behavior the system, would have on incoming request, and no particular reason to use a rule engine and its complexity. Anyway, there are particular cases where BusinessEvents would be a good actor in orchestrating a portion of CEP solutions activities
It allows us to build rule-based model-driven application, to collect, filter, analyze, correlate various business events in our real-time event flow
It makes various business applications/components easy to integrate (loosely decoupled but chained via the events flow) together
Its distributed rule engine and embedded in-memory data grid (ActiveSpace) gives us a lot of flexibility and room to play with a large amount of rules and data with high performance
Python/SQL API, since both are relatively new, still misses a few features in comparison with the Java/Scala option
Steep Learning Curve, it's documentation could be improved to something more user-friendly, and it could also discuss more theoretical concepts than just coding
Better integration with R versions and better debug for R-scripts in Spotfire. There are inconsistencies in syntactic expressions accepted by R-studio and not accepted in Spotfire. Accelerating the debug would be awesome. Having a command like View (data frame) that directly output in the dashboard would be a great accelerator.
TIBCO Business Events is one of the best in business and very well suitable for organization like ours where there are large volumes of data that need to be processed on daily basis. It helps in real time monitoring of data and supports writing complex rules which makes it easier to get the work done. It also helps in fraud detection by identifying suspicious activities and integrate with other systems for a comprehensive view.
Apache Spark is more user-friendly and features higher-level APIs. However, it was initially built for batch processing and only more recently gained streaming capabilities. In contrast, Apache Flink processes streaming data natively. Therefore, in terms of low latency and fault tolerance, Apache Flink takes the lead. However, Spark has a larger community and a decidedly lower learning curve.
I was not part of evaluation of the products in this space in my organization. But I feel BE is better in terms of RIO if compared with some commercial products from Orcle, IBM and SAP. I strongly feel difficulty in using cloud native features is one big shortcoming in current product offering. This will tend customer like us to explore options that are well suited with ur cloud first vision.
