SQL to Hadoop and back again, Part 3: Direct transfer and live data exchange

The third, and final article in my series on migrating data to and from Hadoop and SQL databases is now available:

Big data is a term that has been used regularly now for almost a decade, and it — along with technologies like NoSQL — are seen as the replacements for the long-successful RDBMS solutions that use SQL. Today, DB2®, Oracle, Microsoft® SQL Server MySQL, and PostgreSQL dominate the SQL space and still make up a considerable proportion of the overall market. In this final article of the series, we will look at more automated solutions for migrating data to and from Hadoop. In the previous articles, we concentrated on methods that take exports or otherwise formatted and extracted data from your SQL source, load that into Hadoop in some way, then process or parse it. But if you want to analyze big data, you probably don’t want to wait while exporting the data. Here, we’re going to look at some methods and tools that enable a live transfer of data between your SQL and Hadoop environments.

SQL to Hadoop and back again, Part 3: Direct transfer and live data exchange.

This entry was posted in Articles and tagged , , , . Bookmark the permalink.