Browsing Tag

StreamBase

22 posts

Comparison of Stream Processing Frameworks and Products

See how stream processing / streaming analytics frameworks (e.g. Apache Spark, Apache Flink, Amazon Kinesis) and products (e.g. TIBCO StreamBase, Software AG’s Apama, IBM InfoSphere Streams) are categorized and compared. Besides, understand how stream processing is related to Big Data platforms such as Apache Hadoop and machine learning (e.g. R, SAS, MATLAB).
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Difference between a Data Warehouse and a Live Datamart?

Data Warehouses have existed for many years in almost every company. While they are still as good and relevant for the same use cases as they were 20 years ago, they cannot solve new, existing challenges and those sure to come in a ever-changing digital world. The upcoming sections will clarify when to still use a Data Warehouse and when to use a modern Live Datamart instead.
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Microservices = Death of the Enterprise Service Bus (ESB)? – Slide Deck and Video Recording

In 2015, the middleware world focuses on two buzzwords: Docker and Microservices. Software vendors still sell products such as an Enterprise Service Bus (ESB) or Complex Event Processing (CEP) engines. How is this related? This session discusses the requirements, best practices and challenges for creating a good Microservices architecture, and if this spells the end of the Enterprise Service Bus (ESB).
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TIBCO BusinessWorks and StreamBase for Big Data Integration and Streaming Analytics with Apache Hadoop and Impala

Apache Hadoop is getting more and more relevant. Not just for big data processing (e.g. MapReduce), but also in fast data processing (e.g. stream processing). Recently, I published two blog posts on the TIBCO blog to show how you can leverage TIBCO BusinessWorks 6 and TIBCO StreamBase to realize big data and fast data Hadoop use cases.
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Comparison of Stream Processing and Streaming Analytics Alternatives (Apache Storm, Spark, IBM InfoSphere Streams, TIBCO StreamBase, Software AG Apama)

The article discusses what stream processing is, how it fits into a big data architecture with Hadoop and a data warehouse (DWH), when stream processing makes sense, and what technologies and products you can choose from. Comparison of open source and proprietary stream processing / streaming analytics alternatives: Apache Storm, Spark, IBM InfoSphere Streams, TIBCO StreamBase, Software AG’s Apama, etc.
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Intelligent Business Process Management Suites (iBPMS) – The Next-Generation BPM for a Big Data World

I had a talk at ECSA 2014 in Vienna: The Next-Generation BPM for a Big Data World: Intelligent Business Process Management Suites (iBPMS), sometimes also abbreviated iBPM. I want to share the slides with you. The slides include an example how to implement iBPMS easily with the TIBCO middleware stack: TIBCO AMX BPM + BusinessWorks + StreamBase + Tibbr.
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Enterprise Integration Patterns (EIP) Revisited in 2014

This slide deck revisits Enterprise Integration Patterns (EIP) and gives an overview about the status quo. Fortunately, EIPs offer more possibilities than just be used for modelling integration problems in a standardized way. Several frameworks and tools already implement these patterns. The developer does not have to implement EIPs on his own. Therefore, the end of the slide deck shows different frameworks and tools available, which can be used for modelling and implementing complex integration scenarios by using the EIPs.
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