Last weekend, I read an interesting business use case on Big Data - Cassandra migration. We know about the streaming media leader Netflix; Itz about their Big Data migration from Traditional storage.
About Netflix:
Netflix is the world’s leading Internet television network with more than 48 million streaming members in more than 40 countries. It has successfully shifted its business model from DVDs by mail to online media and today leads the streaming media industry with more than $1.5 billion digital revenue. Netflix dominates the all peak-time Internet usage and its shares continue to skyrocket with soaring numbers of subscribers.
Netflix is the world’s leading Internet television network with more than 48 million streaming members in more than 40 countries. It has successfully shifted its business model from DVDs by mail to online media and today leads the streaming media industry with more than $1.5 billion digital revenue. Netflix dominates the all peak-time Internet usage and its shares continue to skyrocket with soaring numbers of subscribers.
Trigger Point:
In 2010, Netflix began moving its data to Amazon Web Services (AWS) to offer subscribers more flexibility across devices with 'Cloud-First/Mobile-First' Strategy. At the time, Netflix was using Oracle as the back-end database and was approaching limits on traffic and capacity with the ballooning workloads managed in the cloud.
Interestingly, the entire migration of more than 80 clusters and 2500+ nodes was completed with only two engineers
In 2010, Netflix began moving its data to Amazon Web Services (AWS) to offer subscribers more flexibility across devices with 'Cloud-First/Mobile-First' Strategy. At the time, Netflix was using Oracle as the back-end database and was approaching limits on traffic and capacity with the ballooning workloads managed in the cloud.
Interestingly, the entire migration of more than 80 clusters and 2500+ nodes was completed with only two engineers
Use Case:
Systems that understand each person’s unique habits and preferences and bring to light products and items that a user may be unaware of and not looking for. In a nutshell, personalizes viewing for over 50 Million Customers.
Systems that understand each person’s unique habits and preferences and bring to light products and items that a user may be unaware of and not looking for. In a nutshell, personalizes viewing for over 50 Million Customers.
Challenges:
Challenges related to the given use case:
Challenges related to the given use case:
- Affordable capacity to store and process immense amounts of data
- Data Volume more than 2.1 billion reads and 4.3 billion writes per day
- Single point of failure with Oracle’s legacy relational architecture
- Achieving business agility for international expansion
Solution
Big Data Cassandra delivers a persistent data-store
Big Data Cassandra delivers a persistent data-store
- 100% up-time and cost effective scale across multiple data centers
- DataStax expert support the results
- It delivers a throughput of more than 10 million transactions per second
- Effortless creation/management of new data clusters across various regions
- Capture of every detail of customer viewing and log data
The attached Netflix Deployment Diagram is published in Netflix Tech Blog @http://techblog.netflix.com/2012/06/annoucing-archaius-dynamic-properties.html
No comments:
Post a Comment