Everyone knows the time from data-to-action can be critical to winning business, regardless of the variety, velocity, variability and volume of information involved in the process.
And in a world where data is created not only at a pace that is challenging to even ponder but also streams from the Internet of Things (IoT), data lakes are so broad and so deep that making sense of anything in them in real time and reacting accordingly seems unfathomable. Add globally distributed data, and forget about it.
Or maybe not. Because MapR’s latest release, which includes Hadoop has been built for the real time, data-centric enterprise. It leverages table replication features designed to extend access to “big and fast” data enabling multiple instances to be updated in different locations, with all the changes synchronized across them.
“Real time is not just about running a query. It’s also about how and where and how quickly information is processed and the action an organization is going to take,” said Jack Norris, the MapR's chief marketing officer.
Right Offer at the Right Time
If you want an idea of just what this means, consider what happens behind the scenes when you and people all over the planet are playing something like Game of War. You get offers to buy while you’re in the game and, since it’s free to play, the only way Machine Zone, which makes the game, earns money, is when you actually make a purchase.
So reacting to business as it happens with the right offer is a must. Wrong offers are not only missed opportunities but put enough of them together and they could threaten a company’s viability.
That’s one of the reasons why some enterprises are ditching their RDBMS and going with MapR. It offers both a top-rated NoSQL database and Hadoop in nicely bundled solution. MapR, unlike its competitors Hortonworks and Cloudera, is a software company whose aim is to make big data plug and play.
The company’s newest release, which was announced earlier today, was built to include features that accelerate the data-centric enterprise by supporting real-time applications on globally distributed, big and fast data.
Under the Hood
The release includes MapR-DB table replication, which extends access to big and fast data by enabling multiple, active replica clusters across the world with real-time, asynchronous replication. Table replication also delivers real-time disaster recovery to reduce the risk of data loss upon site-wide failure.
This active-active, cross-datacenter capability also enhances global application deployment for Hadoop and big data. Operational data can be stored and processed close to users or devices, while immediately replicating all live data to a central analytics cluster in real time to enable large-scale analytics on enterprise-wide data.
MapR also introduced a new MapR POSIX client, which provides NFS access to applications running on edge nodes with speed and security advantages. The MapR client boosts performance by leveraging compression and parallel access, as well as providing authentication and encryption to ensure secure data access.
A new C API for MapR-DB gives the huge talent pool of application engineers who code in C the ability to write real time Hadoop applications.
Adding Speed, Value
But that’s not all MapR is doing to close the gap between data and decision. It’s also bringing forth three Quick Start Solutions for the MapR Distribution including Apache Hadoop. Namely commonly implemented and high-value Hadoop use cases for Data Warehouse Optimization and Analytics, Security Log Analytics and Recommendation Engines.
The intent is to help customers get faster time to value.
Big data is still a scary, complex idea to much of Enterprise IT. For those who need to get bang for their buck quickly and without much hand holding, it’s certainly worth looking into.
Title image by eschipul.