- Real-Time Analysis In Twitter
Storm can be integrated with Twitter systems for a variety of purposes, including real-time analytics, personalisation, search, revenue optimization, and more. Twitter faces numerous hurdles, including feed personalisation, improved result search, and so on. Storm works seamlessly with the rest of Twitter's infrastructure, including the database systems (Cassandra, Memcached), Mesos and monitoring.
- Real-Time Pipelining In Spotify
Spotify has a number of real-time features, including music recommendations, monitoring, analytics, ad targeting, and playlist creation with streaming over 50 million active users and 10 million subscribers.
Spotify can simply create low-latency fault-tolerant distributed systems with Apache Storm. The personalised Storm architecture subscribes to various user events, decorates the event with entity metadata (such as song genre) retrieved from Cassandra, organises the events by user, and computes various user attributes using an algorithmic combination of aggregation and derivation.
- Online Travel Websites with Real-Time Pipelining
End-users receive real-time metasearch data from affiliates via Apache Storm. Storm's topology concepts alleviate concurrency concerns while also assisting them in continuously integrating, dissecting, and cleaning data. In addition, Storm's tools allow users to make incremental modifications to their data..
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