I choose to compare Yelp, TripAdvisor and Netflix. They all offer service on-line. The similar big data challenges for them is that in face of mountains of data, they changed their data strategy and adjust to the market quickly.
Yelp, launched in 2004, has evolved so much from identifying great restaurants in urban areas to providing user-generated recommendations on a variety of merchants across more than 30 countries, having it service mainly in the form of mobile device. Since January 2013, yelp has experienced high traffic because of huge amounts of users logging in activities, which needs big data infrastructure and data mining. In 2015, site’s star ratings system is being supplemented with objective healthcare data with the corporation with ProPublica. Yelp now uses Amazon Redshift to manage petabyte-scale data warehouse, uses MapReduce extensively and builds its infrastructure on Amazon cloud, and uses Amazon Simple Storage Service to store daily logs and photos of businesses.
TripAdvisor, found in 2000, is a travel website that offers reviews of travel-related content such as hotels, restaurants, and attractions. TripAdvisor is using several Big Data techniques to provide such service, ranging from large-scale real-time analytics, predictive analytics, data mining and statistical modelling. It has also developed a custom Big Data platform, technologies including Hadoop, SQL Server, Hive, Machine-Learning, Redshift, R and Python.