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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Integration of Amazon Redshift Cloud Data Warehouse (AWS SaaS DWH) with Talend Data Integration (DI) / Big Data (BD) / Enterprise Service Bus (ESB)

In this blog post, I will show you how to „ETL“ all kinds of data to Amazon’s cloud data warehouse Redshift wit Talend’s big data components. You need not be a cloud or DWH expert, or an expert developer to integrate with Amazon’s cloud data warehouse Redshift. It is very easy with Talend’s integration solutions. Just drag&drop, configure, do some graphical mappings / transformations (if necessary), that’s it. Code is generated. Job runs. With Talend, you can easily „ETL“ all data from different sources to Redshift and store it there for under $1,000 per terabyte per year – even with the open source version!
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