Big Data: 5 New Technologies to Emerge in 2017
The bubble around Big Data has certainly started to burst and the coming year awaits reasonable developments in the applications of the Big Data world. Well, most of us are now more than familiar with terms like Hadoop, Spark, NO-SQL, Hive, Cloud etc. We know there are at least 20 NO-SQL databases and a number of other Big Data solutions emerging every month. But which of these technologies see prospects going forward? Which technologies are going to fetch you big benefits?
With the year coming to an end, this is a good time to make some predictions on how the Big Data industry will shape up. In this article, I have listed the top 5 technologies to emerge/advance in Big Data in the coming year based upon how Big Data has been doing so far and the upcoming industry trend.
Hadoop has been widely adopted by enterprises for their data warehouse needs in the past year. The trend seems to continue and grow in the coming year as well. Companies that have not explored Hadoop so far will most likely see its advantages and applications.
In terms of the technological developments, Hadoop will come up with features that would make it more enterprise ready. Once Hadoop security projects like Sentry, Rhino etc. gain stability, Hadoop’s implementation will expand across many more sectors and companies can use the solutions without much of security concerns.
All the companies by now have the data and know how to store and process Big Data. The real difference is going to be how fast can they deliver analytics solutions for better business decisions. The Focus in 2017 is going to be Speed. Processing Capabilities of Big Data solutions will certainly increase. Projects like Spark, Storm, Kafka etc. were developed with this aspect in mind. We will see companies advancing from POCs to real world applications with these technologies.
With Internet of Things (IOT) taking front seat, data generation is on its increase. Applications involving IOT will require a perfect scalable solution for managing huge volumes of Data. What other than cloud services can do this better. Advantages of Hadoop on cloud has already been realized by many organisations and technologies pertaining to the coupling of Big Data technologies like Hadoop, Spark, IOT and cloud is expected to be well on rise in the coming year as well.
RDBMS systems have been dominating the database world for decades when structured data formed the major proportion of data in any organization. Looking at the data sources today – Social media data, IOT, sensors etc. – where each one of us is generating volumes of data on a daily basis, it’s clear that the amount of unstructured data is steadily increasing and companies have started realising the potential insights one can gain from such data. Well, now to manage and process such data NO-SQL databases have been the best option in the last few years. Well, this trend will continue to grow. Applications on NO-SQL databases that were mostly POCs are expected to move into deployment phase. The most popular No-SQL databases like MongoDB, Cassandra will continue to be implemented by more vendors. Also graph databases like Neo4j will gain more market.
Applications that simplify data cleaning, data preparation and data exploration tasks is expected to increase. Tools like Tableau with Hadoop has seen increasing popularity in that last 2 years. These products will greatly minimize the effort of the end-users. Companies like Informatica have already shown innovations in this frontier. We can see more such products and more companies working towards such self-service solutions.
To summarize, Big Data is still very much on rise with more adoptions and more applications of the existing technologies and launch of newer solutions related to Big Data security, Cloud integrations, data mining etc.
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