Are The Days Numbered For Hadoop, With Google Cloud /Dataflow – why the days are numbered for Hadoop as we know it.
So, now the biggest revolution is in with the analytic and database technology. Helped by none other than MapReduce, the batch processing technique, this new revolutionary technique is going to change the game completely. Defined as the legacy technology, Google came up with the new arrival of much anticipated Google Cloud Dataflow. This can be stated as a completely new service, under the cloud-based data analytics. As per the spokesperson of Google, this cloud program is enough to supersede the MapReduce. There are various corporations and firms, which have already pumped billions into the Hadoop segment, but now Google is changing the game, altogether.
Flexible analytic pipelines
Google make it a huge turning point, by abandoning MapReduce, quite some time now. It was too hard to build flexible and much-needed analytic pipelines, with this software. So, what are they up to now? After much speculations and leaks, Goggle came up with real-time capability and has optimized the algorithms, to match up with the growing demands. This can offer you with none other than faster track results. The concept of MapReduce has also been refined, in order to increase the visibility rate in terms of productivity and usability.
To a completely new track
Google has taken the concept of data-driven business to a completely new level, and here timely insights have now become critical. Therefore, you are likely to come to terms of reliable, robust and fault tolerance architecture. Moreover, Google has now refined the OS platform, to operate at massive level, in various data centers. Thus, it can be well stated that Dataflow has now won over millions of users, with the positive features, mentioned above. It can be well stated as the life of any reliable analytic developer. It is way easier, when compared with the online or real time tracking services, when compared with the computation services.
Hiding the complexity
Even though the features are practically endless, but one of the most prominent features of Dataflow is that it can help in hiding the complexity. You just need to subscribe for publish-subscribe message broker, in order to avail real-time feed. Moreover, you need to take extra steps for processing the messages and deal with the outputs, to another message broker. On the other hand, you have the liberty to access the file system of Google, which you can read and write directly, from the saved documents. Moreover, you can even access the data, with the help of BigQuery tablets.
Pipeline is same
As the associated pipeline is more or less same, therefore; you can reuse the code as written for separate batch processing. These are primarily related to online processing jobs. Moreover, the presentation, related with Google I/O can suggest a proper mix of batch processing jobs and real-time services. Well, you need to look hard for the details as those are about to be passed by the leading Google team. This segment has the reliable power mode to optimize the pipelines, crunched by data. This field is highly rich in feature, and the way more complicated. Therefore, the growth of Dataflow is an inevitable truth, now.