With the advent of Splice Machine and the release of Hive 0.14 we are seeing Hadoop’s role in the data center continue to grow. Both of these technologies support limited transactions against data stored in HDFS.
The Future of Big Data
With some guidance, you can craft a data platform that is right for your organization’s needs and gets the most return from your data capital.
Now, I would not suggest moving your mission-critical ERP systems to Hive or Splice Machine, but the support of transactions is opening up Hadoop to support more use cases, especially those use cases supported by RDBMS based data warehouses. With transaction support there is a more elegant way to handle slowly changing dimensions of all types in Hadoop now that records can be easily updated. Fact tables with late-arriving information can be updated in place. With transactional support, Master Data can be supported more efficiently. The writing is on the wall: more and more of the functionality that has been historically provided by the data warehouse is now moving to the Hadoop cluster.
To address this ever-changing environment, enterprises must have a clear strategy for evolving their Big Data capabilities within their enterprise architecture. This Thursday, I will be hosting a webinar, “Creating the Next-Generation Big Data Architecture,” where we will discuss Hadoop’s different roles within in a modern enterprise’s data architecture.
