Adoption of in-memory technology solutions is happening faster than ever. This stems from a three pronged demand – first, a greater number of users, analysts, and businesses need access to data. Second, the number of transactions is increasing globally, so companies need faster ingest and analytics engines. Finally, performance inconsistencies are the nail in the coffin for companies competing in the on-demand economy – these enterprises need the responsiveness in-memory technology...
by Emily Friedman
by Kevin White
Setting the Stage for Spark
With Spark on track to replace MapReduce, enterprises are flocking to the open source framework in effort to take advantage of its superior distributed data processing power.
IT leads that manage infrastructure and data pipelines of high-traffic websites are running Spark–in particular, Spark Streaming which is ideal for structuring real-time data on the fly–to reliably capture and process event data, and write it in a format that can immediately be queried by...
by Neil Dahlke
In preparation for Open World, I asked some of our engineers to recreate a demo that Oracle has been using over the last year to show off their “in-memory option.” It’s impressive to look at: the demo shows the database searching through billions of records from Wikipedia search trend data for popular terms in less than a second.
The thing about Oracle’s demo is it runs on a gigantically expensive server. In fact it is the biggest one they have at 32TB of RAM and hundreds of CPU cores....
by Nikita Shamgunov