Hadoop The Future of Big Data Solutions - Volantech - Eng
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Hadoop The Future of Big Data Solutions – Volantech English

Hadoop-based Java under Apache license offers a solution to handle the large data processing rapid, reliable, flexible and cost both structured data and unstructured data.

 

Hadoop is a software framework allows library form processing and data distribution are very large with a simple programming models. This framework is designed to improve the connection only between one server with thousands of other server machines are initially in the form of local computing and storage.

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To make the process of large-sized data Hadoop Map Reduce applying Google technology and the Google File System (GFS) as its base, where the application is divided into small sections, but can be executed and the execution is repeated at each point to its cluster. In a distributed file system (Hadoop Distributed File System-HDFS) will store data at the point with a large bandwidth node on the cluster. Both MapReduce and HDFS has been designed to automatically handle failures or errors at the point node.

There are many large-scale data projects using Apache Hadoop nowadays. Since 2006, Hadoop User continues to increase.

Here’s a picture of Hadoop users

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(source: https://www.mapr.com, Image © Friedman and Dunning 2015, from Chapter 1 of “Real World Hadoop”)

When this has been a lot of projects that use Apache Hadoop to manage data without using SQL. SQL solutions in the face of large-sized data sometimes yielding data that can not be solved. The days will come, various industries  will use Big Data to handle the amount of data continues to grow every day.

According to McKinsey Global Institue’s research, the big data implementation has improved significantly for $610 million/year industry (covering manufacturing and retail services). This study estimates that in the 80% will use Hadoop solution to address data growth. Because many companies will work to obtain sufficient information to support decision making. This assessment is based on data paad 2015 with 90% of data created 2 years came from social networking network, client transactions, web browsing, and so on.

Based on data from CbInsight.com few industries that now have adopted Hadoop as Bussiness Intelligence, Analytics and Performance Management both from the leaders, advertisers, sales and marketing, stock market, and Advertising Networks. The following table Hadoop users by rank:

 

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Advantages Hadoop in handling big data as follows:

  1. Having the ability to manage and store different types of data quickly. With a fast process, requiring fast computational capability as well. Having clusters that contain a distributed file system
  2. Having a hardware fault tolerance, it is useful to protect the processes that are at the nodes are in trouble immediately automatically transferred to the other node so it certainly will not fail computing. Data storage is also processed automatically copy
  3. Hadoop has the flexibility of the data to be used. Unlike relational databases typically, the data must be stored before use. Making it easy to access data Bary with different types.
  4. Hadoop is one of the open source framework for storing large data
  5. Having the ability to handle data growth as well as to have the administration of the data

 

For project developers with Hadoop please contact dev@volantech.io

 

©Written by : Satriadi Wijaya Tjoa S.Kom

*Please find the below links for further references :

https://en.wikipedia.org/wiki/Apache_Hadoop

http://hadoop.apache.org/

http://hortonworks.com/apache/hadoop/

http://www.mckinsey.com

http://www.sas.com/en_us/insights/big-data/hadoop.html

https://wiki.apache.org/hadoop/PoweredBy

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