@sushil nagur I agree with both @Graham Martin and @ccasano. Instead of talking about tools which you already know from above answers, I'll talk about why CIOs prefer Hortonworks for offloading their existing ETL jobs. As Graham mentions, we have partners like Informatica, Talend, Pentaho, Syncsort that you can use to write your ETL jobs in Hadoop. What this gives you is faster time to market which is the same story as previous ETL tools. They save time from writing code and your ETLs manually. Prevents bugs that you may have if you were to write your own code. Under the hood, they use similar technologies like Spark, Map/Reduce and even same fast connectors that Sqoop uses. So why use Hortonworks? Because where is the storage engine where all the processing is happening? Without Hortonworks, in the legacy/existing systems, CIOs are paying significantly higher cost per TB of doing the ETL. Some companies are even doing ELT which means they first load data into their data warehouse and then use the processing power of that system to perform transformation. This takes away very expensive resources from reporting/adhoc queries from business which is what the EDW was purchased for to begin with. When you offload those jobs onto Hadoop, you free up all that capacity from these systems and free up the processing power for reporting and business use. Your per TB cost of doing ETL in Hadoop is fraction of what it is in traditional ETL systems. This is the main motivation of offloading ETL in Hadoop. You perform ETL in Hadoop and then push your final result into your EDW.
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