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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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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Systems Integration in the NoSQL Era with Apache Camel and Talend (MongoDB, Neo4j, HBase, AWS S3, Hazelcast, CouchDB)

In February 2013, I was at ApacheCon NA 2013 in Portland, Oregon, USA. My session was named “Systems Integration in the NoSQL Era with Apache Camel”. I showed how to integrate several different NoSQL databases such as MongoDB (document), Neo4j (graph), HBase (column), AWS S3 (key-value), or Hazelcast (in-memory).
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