“As a developer, understanding the Hadoop ecosystem can make you very valuable. Companies are leveraging it for more projects each day.” – Thomas Henson: Senior Software Engineer, Certified ScrumMaster & Technical Author at Pluralsight.
Over the past decade, the world has seen the launch of a multitude of ambitious frameworks and solutions aimed at tackling all your Big Data challenges, and we found which of the hadoop-integrated platforms were dominating the market.
#1 – CLOUDERA ENTERPRISE
The only platform with the native Hadoop Search engine. With high performance, low cost and advanced optimisation features, Cloudera Enterprise is among the most popular choices for enterprises who want fast, easy and secure Big Data projects.
“Cloudera supplements everything we liked about Hadoop by providing a clear path to being production-ready, ease of management, and top performance. We now have the agility to quickly react to new situations and deliver market-leading capabilities to our clients.” – CounterTack.
#2 – APACHE SPARK
Internet powerhouses like Netflix, Yahoo and eBay are loving Apache Spark, having deployed it at massive scale. Known for its speed, ease of use and generality, Apache Spark supports Scala, Python and Java and boasts speed 100-times faster than Hadoop for large-scale data processing.
“Spark … is what you might call a Swiss Army knife of Big Data analytics tools.” – Reynold Xin: Berkeley AmpLab Shark Development Lead.
#3 – APACHE HIVE
“Hive is the closest thing to a relational-database in the Hadoop ecosystem.” – Pluralsight.
Hive is data warehousing framework that allows for structuring and querying data using a language called HiveQL to write complex MapReduce over structured data in a distributed file system. Companies like Facebook, Qubole Inc. and Tata Consultancy Services are using this software to read, write and manage large datasets.
#4 – APACHE PIG
With big-time users like LinkedIn, Twitter and Salesforce, Apache Pig is popular for its ease of programming and customisation capabilities. It transforms large data sets with its own SQL-Like language. While applications like Hive are used for structured data, Pig is famous for transforming semi-structured and unstructured data, allowing developers to write complex MapReduce jobs without having to write them in Java.
#5 – APACHE SQOOP
“Not just a good general-purpose tool, but also a high-performance solution.” – Justin Kestelyn: Group Product Marketing Manager, Google Cloud Platform- Data Processing & Analytics.
Highly utilised for its efficiency and convenience, Sqoop allows developers to transfer data from a relational database into Hadoop, with significant opportunities for optimisation. Bundled with various connectors, it can be used for popular database and data warehousing systems such as such as Teradata, Netezza, Oracle, MySQL, Postgres, and HSQLDB.
#6 – APACHE ZOOKEEPER
The ultimate enabler of highly reliable distributed coordination in the Hadoop Ecosystem. ZooKeeper provides centralised services for configuration, synchronisation and group services.
“We use ZooKeeper extensively for discovery, resource allocation, leader election and high priority notifications. Our entire service is built up of multiple systems reading and writing to ZooKeeper.” – Konrad Beiske: Software Engineer at Elastic.co.
For more resources, please see the links below:
The Hadoop Ecosystem: