Hadoop
Facebook and Yahoo’s baby, available to all!
Hadoop is a range of projects and free tools from the Apache foundation that are used to store and process enormous volumes of data.
Developed by Facebook and Yahoo, Hadoop has really taken off and is now at the heart of Open Source innovation and Big Data.
Smile & Hadoop
For several years, Smile has been working on the development of a Big Data centre of expertise that provides training and certification for consultants and developers in Hadoop technologies such as Hortonworks Data Platform, Hortonworks Data Flow, Elastic…
What is the aim? To transfer all of our expertise and know-how about development, advice and operation of Big Data platforms.
Today, Smile is recognised for its expertise in the implementation and operation of platforms, principally for large accounts.
Technical talk is bypassed to focus instead on ways to connect with businesses and to work on practical applications!
Features
| Studied version |
3.0.0
|
| Licence |
Apache
|
| Language |
Java
|
| Creation year |
2006
|
Hadoop is a range of projects and free tools from the Apache foundation that are used to store and process enormous volumes of data.
Developed by Facebook and Yahoo, Hadoop has really taken off and is now at the heart of Open Source innovation and Big Data.
http://hadoop.apache.org/releases.html
Hadoop, power and simplicity for everyday use
With an Open Source and free framework, Hadoop’s principal aim is to facilitate data processing in a distributed way.
There are several Hadoop distributions available including Hortonworks, Cloudera and MapR.
The Big Data ecosystem is in a state of perpetual evolution. New products and projects appear on the market on a monthly basis.
How can businesses maintain stability and reliability in this context? These are precisely the Hadoop distributions that bring with them the necessary guarantees to provide assurances for deployments and to ensure that solutions are compatible with each other.
Multiple solutions available from the Hadoop ecosystem open up a range of possibilities:
- Operational data Storage / ODS (HDFS or Hbase) or storage in a data warehouse (Hbase or Hive)
- Parallel integration and processing of data (YARN/Map-Reduce, Pig)
- Request and analysis of mass data (Hive+YARN/Map-Reduce, Pig)
- Data mining (Mahout)
- In addition, various softwares come already connected such as Apache Pig, Apache Hive, Apache HBase, Apache Phoenix, Apache Spark, Apache ZooKeeper, Cloudera Impala, Apache Flume, Apache Sqoop, Apache oozie or Apache Storm.
Would you like to find out more? Dive deeper into the subject of Hadoop with Smile’s blog articles!
- A comparison of SQL user interfaces and Big Data/ NoSQL data warehouses
- Analysing the use of websites with SQL and high traffic volumes with MongoDB and Hadoop Hive
- Hadoop 2.0: MaPreduce becomes YARN and offers new functionalities
- Integrating data from the IoT in real time with Talend Real-Time Big Data
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