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Jul 11, 2022 · Most of the YouTube data is stored in the Google Modular Data Centers. A modular data center is portable and can be placed wherever the data storage capacity is required. Since YouTube was bought by Google in 2006, it stands to reason that the YouTube data is stored in the Google Modular Data Centers. There are mainly 5 or 6 Google data centers ...
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Now yes, youtube, netflix, and others dwarf this, but let's say a thousand times larger. So $500M. Doable. Where that smaller system can store 300k+ movies (12 per day@2hr per @100 chans@270 days), the large system stores 300M movies. Maybe a bit much, so scale it down a bit, maybe $100M. 60M movies.
- Introduction
- Backend Infrastructure
- The Need For Vitess
- Master-Slave Replica
- Sharding
- Disaster Management
- Vitess – A Database Clustering System For The Horizontal Scaling of MySQL
- Deployment on The Cloud
- CDN
- Data Storage – How Does YouTube Stores Such An Insane Amount of Data?
YouTube started its journey in 2005. As this venture capital-funded technology startup gained traction, it was acquired by Google in November 2006 for US$1.65 billion. Before they were acquired by Google, the team comprised: 2 system admins 2 software architects that focused on the site’s scalability 2 feature developers 2 network engineers 1 DBA
YouTube’s backend microservices are written using Python, C, C++, Java with Guice framework, and Go. JavaScript is used for the user interface. MySQL is the primary database powered by Vitess, a database clustering system for horizontal scaling of MySQL. Memcache is used for caching and Zookeeper for node coordination. Popular videos are served fro...
The website started with a single database instance. As it gained traction, to meet the increasing QPS (Queries Per Second) demand, the developers had to horizontally scale the relational database.
Replicas were added to the master database instance. Read requests were routed to both the master and the replicas parallelly to cut down the load on the master. Adding replicas helped get rid of the bottleneck, increased read throughput and added durability to the system. The master node handled the write traffic, whereas both the master and the r...
The next strategy was to shard the database. Sharding is one of the ways of scaling a relational database besides others such as master-slave replication, master-master replication, federation etc. Sharding a database is something that is far from trivial. It increases the system complexity by a significant amount and makes management harder. Regar...
Disaster management means having contingencies in place to survive power outages, natural disasters like earthquakes, fires, etc. It entails having redundancies in place and the user data backed up in data centers located in different geographical zones across the world. Losing user data or the service being unavailable wasn’t an option. Having sev...
Vitessis a database clustering system that runs on top of MySQL and enables it to scale horizontally. It has built-in sharding features that enable developers to scale their database without adding any sharding logic to the application. Something along the lines of what a NoSQL database does. Vitess Architecture Image Source Vitess also automatical...
Vitess is cloud-native and suits well for cloud deployments as with it the database capacity can be incrementally augmented just like it happens in the cloud. It can run as a Kubernetes-awarecloud-native distributed database. At YouTube, Vitess runs in a containerized environment with Kubernetes as the container orchestration tool. In today’s compu...
YouTube uses low-latency, low-cost content delivery using Google’s global network. It leverages the globally distributed Edge POPs (Points Of Presence) to enable its client to fetch data a lot quicker as opposed to fetching it from the origin server. Upto this point I’ve discussed the database and backend tech used at YouTube. Time to talk about st...
The videos are stored in the hard drives in warehouse-scale Google data centers. The data is managed by the Google File System and BigTable. GFS Google File Systemis a distributed file system developed by Google to manage large-scale data in a distributed environment. BigTableis a low latency distributed data storage system built on Google File Sys...
Jul 17, 2024 · How Much Data Does YouTube Store Daily? 1. Video Uploads: ... - 720,000 GB/day = 720 TB/day. This means YouTube needs about 720 Terabytes of storage every day just for new video uploads ...
Most estimates conclude that YouTube has at least one exabyte (1,000,000 terabytes) of storage space in its data centers. To help illustrate the full enormity of this, popular webcomic XKCD broke down an estimate of Google's potential storage capacity visually. So how exactly does YouTube store their global digital data? Understanding YouTube's ...
Youtube has the space because it's owned by Google. Togther, youtube and Google bring in a ton of revenue, allowing them to build many gigantic server farms to store the tons of data that it stores. This video is over 4 years old so the technology has changed, but it gives you an idea of the sheer size of a Google data center.
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Jan 15, 2020 · Back-of-the-envelope calculations are often expected in system design questions. They help logically state the parameters influencing a result, and estimatin...
- 13 min
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- Gaurav Sen
