Apache Camel and Talend ESB: Management and Monitoring of Integration Routes and SOAP / REST Web Services (JMX, OSGi, logstash, ElasticSearch, Kibana, hawtio)

A question every customer asks me: How can you manage and monitor integration routes implemented with Apache Camel and / or Talend ESB (which is based on Apache Camel and also available as open source version). This blog post will show different alternatives to answer this question. The good news first: As Apache Camel and Talend ESB are based on open standards, you can use your own frameworks and tools if tooling of the product is not sufficient. So, I will not talk just about features of Apache Camel or Talend ESB, but also about additional options.
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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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Book Review: “Getting Started with NoSQL” by Gaurav Vaish (Packt Publishing)

“Getting Started with NoSQL” is a new book by PACKT PUBLISHING. It gives an introduction to different NoSQL concepts and products. Besides, it explains the differences to SQL databases and when to use which one. With 150 pages, the book is not extensive, but sufficient. It is a good introduction to NoSQL databases for developers, architects and decision makers.
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You are not Facebook or Google? Why you should still care about Big Data and Apache Hadoop Ecosystem (Pig, Hive, Hortonworks, Cloudera, MapR, Informatica, Talend)

In March 2013, I was at 33rd Degree – “A Conference for Java Masters”. I had two talks, including a new one: “You are not Facebook or Google? Why you should still care about Big Data”. It is a great talk to give an overview about big data, especially from a business perspective (paradigm shift, business value, challenges). However, I also talk about alternatives for big data from a technology perspective, mainly about the defacto standard Apache Hadoop, its ecosystem, distributions, and tooling (i.e. big data suites).
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