2015 was another outstanding year for leading enterprises and startups as they endow dollars in open source platforms and technologies to handle volumes of data and improve business decisions. Technology has come a long way in analytics, attempting to enforce productive solutions internally before presenting information to the consumers and users.
In the past five years, social media giants like Facebook, Twitter, LinkedIn, and Google have underpinned powerful and scalable computing ecosystem to manage data and filter down a broad range of business operations. The question arises why do we need to know about the internal systems of these social channels?
It is indeed beneficial for Developers and Analysts to know what all software and technology are these internet firms adopt and support so that you can develop your skills and knowledge up to their standards and get high paid jobs in top companies. Let’s recognize some of the innovative, open source platforms and tools the social media giants embrace and promoting for wider purposes.
No wonder, Google is the largest engine on the internet consisting of all kinds of content for all types of audiences across the globe. MapReduce is one of its prominent creations, which allows it to analyze, capture, search, store, transfer and visualizes huge data across clusters of network servers. As technology has progressed, Google has adopted Hadoop, which again is based on MapReduce and supports map and reduce options for processing large sets of data within a distributed file system – HDFS.
Hadoop is now a major selling technology platform for enterprises and business groups like Cloudspace, Alibaba, Adobe, Yahoo!, Accenture, Cognizant, AOL and almost each IT company and E-commerce performers. Hadoop and MapReduce Training are hot topics among Big Data Experts and Professionals as they move forward in their careers.
Apache Cassandra was developed at Facebook by Avinash Lakshman and Prashant Malik to boost their inbox search. In technical terms, Cassandra is an open source database distributed management system (NoSQL) created to develop massive data across multiple commodity servers, imparting high availability with not a single point of failure.
Having a data model that establishes dynamic control over data layout and format, Cassandra is preferred as it does not have a traditional relational data model. Cassandra has its latest version 2.2.2 released in October 2015. Gaining popularity among top companies, Twitter, Apple, Netflix are a few well-known tech firms that are using Cassandra for their database processes.
To analyze large amounts of data in real-time. Twitter open sourced Storm in 2011. After associating with the major incubator, Apache, Storm got immense recognition for its distributed, fault-tolerant, real-time computation system having the processing power to scale multiple nodes – up to 1 Million, 100-byte messages per second per node. Twitter claims Storm is an only Hadoop framework for processing streaming data.
In an effort to improve and enhance Storm capabilities, Twitter has shown interest towards a new platform, i.e. Heron. As the data is reaching to billions of events per minute, team leaders of Storm are looking forward to ensuring data accuracy, resiliency and handling failure scenarios by adopting Heron as the new processing system.
“One of the most famous open source projects is: Kafka, a distributed publish/subscribe mechanism. Kafka falls into the category of systems that allow us to move massive amounts of data at scale,” says VP of Engineering at LinkedIn He further mentions, “It’s a distributed and scalable commit-log based event system.”
According to Data Analysts at LinkedIn, they receive over 13 million messages per second, which equals to 2.75 Gigabytes of data each second. Created by this business networking firm in 2011, Kafka is a panacea to this big data generation. LinkedIn runs over 1100 Kafka brokers arranged in more than 60 clusters, to handle this per second numbers.
Lately, the Engineers and Creators of this technology are focusing on developing next generation Apache Kafka with the name Confluent. In order to enable multi-tenant operations, high throughput, scalable data integration across a variety of data sources and cater to the increasing requirements of enterprise consumers, Confluent will prove to be a valuable solution.
About the Author: Vaishnavi Agrawal loves pursuing excellence through writing and has a passion for technology. She has successfully managed and run personal technology magazines and websites. She is based out of Bangalore and has an experience of 5 years in the field of content writing and blogging. Her work has been published on various sites related to Hadoop, Big Data, Business Intelligence, Cloud Computing, IT, SAP, Project Management and more.