How to: Relational database management system (RDBMS)
A relational database like SQL is a collection of data items organized in tables.

**ACID** is a set of properties of relational database [transactions](https://en.wikipedia.org/wiki/Database_transaction).

* **Atomicity** - Each transaction is all or nothing
* **Consistency** - Any transaction will bring the database from one valid state to another
* **Isolation** - Executing transactions concurrently has the same results as if the transactions were executed serially
* **Durability** - Once a transaction has been committed, it will remain so

There are many techniques to scale a relational database: **master-slave replication**, **master-master replication**, **federation**, **sharding**, **denormalization**, and **SQL tuning**.

#### Master-slave replication

The master serves reads and writes, replicating writes to one or more slaves, which serve only reads.  Slaves can also replicate to additional slaves in a tree-like fashion.  If the master goes offline, the system can continue to operate in read-only mode until a slave is promoted to a master or a new master is provisioned.
Source: Scalability, availability, stability, patterns
##### Disadvantage(s): master-slave replication

* Additional logic is needed to promote a slave to a master.
* See [Disadvantage(s): replication](#disadvantages-replication) for points related to **both** master-slave and master-master.

#### Master-master replication

Both masters serve reads and writes and coordinate with each other on writes.  If either master goes down, the system can continue to operate with both reads and writes.
Source: Scalability, availability, stability, patterns
##### Disadvantage(s): master-master replication

* You'll need a load balancer or you'll need to make changes to your application logic to determine where to write.
* Most master-master systems are either loosely consistent (violating ACID) or have increased write latency due to synchronization.
* Conflict resolution comes more into play as more write nodes are added and as latency increases.
* See [Disadvantage(s): replication](#disadvantages-replication) for points related to **both** master-slave and master-master.

##### Disadvantage(s): replication

* There is a potential for loss of data if the master fails before any newly written data can be replicated to other nodes.
* Writes are replayed to the read replicas.  If there are a lot of writes, the read replicas can get bogged down with replaying writes and can't do as many reads.
* The more read slaves, the more you have to replicate, which leads to greater replication lag.
* On some systems, writing to the master can spawn multiple threads to write in parallel, whereas read replicas only support writing sequentially with a single thread.
* Replication adds more hardware and additional complexity.

##### Source(s) and further reading: replication

* [Scalability, availability, stability, patterns](http://www.slideshare.net/jboner/scalability-availability-stability-patterns/)
* [Multi-master replication](https://en.wikipedia.org/wiki/Multi-master_replication)

#### Federation
Source: Scaling up to your first 10 million users
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.

##### Disadvantage(s): federation

* Federation is not effective if your schema requires huge functions or tables.
* You'll need to update your application logic to determine which database to read and write.
* Joining data from two databases is more complex with a [server link](http://stackoverflow.com/questions/5145637/querying-data-by-joining-two-tables-in-two-database-on-different-servers).
* Federation adds more hardware and additional complexity.

##### Source(s) and further reading: federation

* [Scaling up to your first 10 million users](https://www.youtube.com/watch?v=kKjm4ehYiMs)

#### Sharding
Source: Scalability, availability, stability, patterns
Sharding distr