Hadoop and the Data Warehouse: When to Use Which

Hadoop and the Data Warehouse: When to Use Which

Hadoop and the data warehouse will often work togehter in a single information supply chain. When it comes to Big data, Hadoop excels in handling raw, unstructured and complex data with vas programming flexibility. Data warehouses also manage bog structured data, integration subject areas and providing interactive performance BI tools. It is rapidly becoming symbiotic relationship. Some difference are clear, and identifying workloads or data that runds best one or other will be dependent on your organization and use cases. As with all platform selections, care analyais of the business and technical requirements should be done before platform selection to ensure the best outcome. Having both Hadoop and a data warehouse onsite greatly helps everyone learn when to use which.

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Luca Rodolfi

Insightful Data, BI & AI

8 年

a 2011 whaitepaper... a bit old...

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.Rogier Werschkull

Head of Data @ Coolgradient | Data-analytics trainer | Rockstar & AI artist @ night ;) | Love calling bullshit

8 年

Bull####, data warehousing is a concept, it is about functionality. Hadoop is an ecosystem of products. Putting them together in a table is just plain nonsense and dangerous in my opinion!

Ron Dunn

Performance Specialist at Snowflake - The Data Cloud

8 年

I think that's a reasonable positioning of the technologies. One point you might like to consider is the use of Hadoop as a pre-ELT data store, or Data Lake, for capturing large volumes of data from which a DW might be supplied when the use of the data has been confirmed. I think it sits nicely alongside your sandbox and provisional points.

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Ram Chandra( Big Data Consultant )

Big data Solution Architect at Princeton

8 年

Good one

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Veera - B.Tech., MBA.

Looking for opportunity as Big Data Analyst/Scientist

8 年

nice article...

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