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Update "Scaling up to your first 10 million users" link (#411)

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@ -806,7 +806,7 @@ Systems such as [Consul](https://www.consul.io/docs/index.html), [Etcd](https://
<p align="center"> <p align="center">
<img src="http://i.imgur.com/Xkm5CXz.png"/> <img src="http://i.imgur.com/Xkm5CXz.png"/>
<br/> <br/>
<i><a href=https://www.youtube.com/watch?v=w95murBkYmU>Source: Scaling up to your first 10 million users</a></i> <i><a href=https://www.youtube.com/watch?v=kKjm4ehYiMs>Source: Scaling up to your first 10 million users</a></i>
</p> </p>
### Relational database management system (RDBMS) ### Relational database management system (RDBMS)
@ -872,7 +872,7 @@ Both masters serve reads and writes and coordinate with each other on writes. I
<p align="center"> <p align="center">
<img src="http://i.imgur.com/U3qV33e.png"/> <img src="http://i.imgur.com/U3qV33e.png"/>
<br/> <br/>
<i><a href=https://www.youtube.com/watch?v=w95murBkYmU>Source: Scaling up to your first 10 million users</a></i> <i><a href=https://www.youtube.com/watch?v=kKjm4ehYiMs>Source: Scaling up to your first 10 million users</a></i>
</p> </p>
Federation (or functional partitioning) splits up databases by function. For example, instead of a single, monolithic database, you could have three databases: **forums**, **users**, and **products**, resulting in less read and write traffic to each database and therefore less replication lag. Smaller databases result in more data that can fit in memory, which in turn results in more cache hits due to improved cache locality. With no single central master serializing writes you can write in parallel, increasing throughput. Federation (or functional partitioning) splits up databases by function. For example, instead of a single, monolithic database, you could have three databases: **forums**, **users**, and **products**, resulting in less read and write traffic to each database and therefore less replication lag. Smaller databases result in more data that can fit in memory, which in turn results in more cache hits due to improved cache locality. With no single central master serializing writes you can write in parallel, increasing throughput.
@ -886,7 +886,7 @@ Federation (or functional partitioning) splits up databases by function. For ex
##### Source(s) and further reading: federation ##### Source(s) and further reading: federation
* [Scaling up to your first 10 million users](https://www.youtube.com/watch?v=w95murBkYmU) * [Scaling up to your first 10 million users](https://www.youtube.com/watch?v=kKjm4ehYiMs)
#### Sharding #### Sharding
@ -1122,7 +1122,7 @@ Sample data well-suited for NoSQL:
##### Source(s) and further reading: SQL or NoSQL ##### Source(s) and further reading: SQL or NoSQL
* [Scaling up to your first 10 million users](https://www.youtube.com/watch?v=w95murBkYmU) * [Scaling up to your first 10 million users](https://www.youtube.com/watch?v=kKjm4ehYiMs)
* [SQL vs NoSQL differences](https://www.sitepoint.com/sql-vs-nosql-differences/) * [SQL vs NoSQL differences](https://www.sitepoint.com/sql-vs-nosql-differences/)
## Cache ## Cache