Gluent Demo Series: Offload
Gluent Data Platform will synchronize your relational database data to modern storage and processing platforms, enabling organizations to take advantage of true data virtualization. The hybrid tables in the RDBMS require zero application or query modifications and will continue to run as if the data still resided in the original database schema. The first step to implementing the hybrid, new world of data storage and processing is to offload data from the RDBMS to a distributed system like Hadoop. Gluent Offload can even keep the data synchronized, with incremental update and change data capture functionality. Watch the videos below to learn more!
Offloading data from the RDBMS to modern data storage processing platforms, such as Hadoop, is a well known function of Gluent Data Platform. But did you know that the Offload component can also perform change data capture (CDC) and incrementally update the data in Hadoop? Have a look!
Gluent Data Platform can be used to implement a hybrid table, with a majority of the data stored and processed in Hadoop and the remaining data still in the relational database. We call this a 90/10 approach to offloading, but really any percentage of data can be moved to modern storage and data processing platforms to meet your enterprise data needs. Use the Gluent Offload Incremental Partition Append functionality to ensure the “cold”, least active data is synced to Hadoop. Here’s a quick video demonstration.
The Incremental Update functionality of Gluent Data Platform doesn’t require the insert, update, and delete transactions to occur against data that lives in the relational database. As you’ll see in this demo video, the data can be completely offloaded to Hadoop and dropped from the relational database and Gluent will still perform the incremental update!
Want to see more? Give us a shout!