- Now, let's talk about Amazon Aurora.
With Amazon Aurora, we gain access to a database
that is compatible with, that is essentially
a drop-in replacement for MySQL 5.6 or Postgres 9.6.
And so, for most used cases, not all but most used cases,
you can see companies have seen three to five times
performance increase with no changes to the schema
and no changes to code.
Now, one of the great things about Aurora
besides being a very performant replacement
for MySQL or Postgres is that we get a storage plane
up to 64 terabytes that is auto-scaled
and inherently replicated, right?
Now, if you were to compare this.
If two RDS, let's say running Postgres on RDS.
With RDS, if you wanted a larger storage platform,
you would have to create an entirely new database instance
to gain access to a larger underlying storage.
But with Amazon Aurora, the storage
just grows automatically and it grows in certain increments.
As your dataset grows, the underlying storage volume
will automatically grow to accommodate that dataset.
There's nothing for you to do.
You don't have to pre-provision a certain amount of storage.
It just automatically grows up to 64 terabytes.
And there's nothing we need to do with Aurora
in order to ensure that we have multiple copies
that are live.
It automatically maintains numerous copies
across numerous availability zones, right?
So a lot of that high availability fault tolerance
and data durability, it's already built-in to Amazon Aurora.
We also get up to 15 read replicas,
very easy read replica creation.
And then we also gain access
to what we call Aurora Multi-Master
where we can have multiple masters to which we can write to.
Not only can we have those 15 read replicas
but we can also write to multiple masters
and those are also the replication between those two
is managed by Amazon, by the Aurora service.
And lastly, we also have Aurora Serverless.
Now, with normal Aurora, even though Amazon is managing
all of the underlying infrastructure.
The storage plane, the compute service and everything else.
There's still something for us to manage,
there's still an instance of Aurora that we need to create
and modify options on.
But with Aurora Serverless, there isn't.
There's nothing there until we actually need it.
So Aurora Serverless is more like on demand
when our application needs that database engine,
it boots up, it makes itself available,
we do our writes, we do our reads
and then we don't need it anymore, it goes away.
So we have a lot of really and of course,
we'll take a look a closer look at Aurora Serverless
in an upcoming section.
But of course, remember the key point here
is that Amazon Aurora can be a very performant
drop-in replacement for MySQL or Postgres.