Hello, and welcome to this section on databases.
So I'm doing a quick intro because at the exam
you will have to choose the right database
for your workload, and there are a lot of managed databases
on AWS to choose from.
So it's mainly based on the architecture
of the question is asking, and so, is it write-heavy,
is it read-heavy, is it balanced workload?
What does it need?
Is it going to change or fluctuate during the day?
How much data is going to be stored and for how long?
Will it grow? What's the average object size?
How often are there access and how are the text?
What about data durability?
What is the source or truth for your data?
Do you have any latency requirements?
Any concurrent user requirements?
What is the data model?
How are you going to query the data, joins?
Is it structured? Is it semi-structure?
Do you need a strong schema or do you need more flexibility?
Do you want to include reporting
on top of your database or not?
Do you want search?
Do you want a relational database or NoSQL?
Are there any license cost?
Do you wanna switch to Cloud Native databases
such as Aurora and so on.
So, of course, based on the question
you have a different answer,
but just to give you the kind of dimensions
and the kind of avenues the questions can be geared towards
for helping you choose the right database.
But don't worry, we will see all the different databases
in this section and summarize them.
So first we have the RDBMS databases.
That means you're using SQL
or you wanna do online transaction processing.
So you have RDS and Aurora, and these databases are great
if you wanna do joins.
Don't worry, by the way, we'll go into a deep dive
in all these databases
so you don't have to remember everything.
Then we have the category of the NoSQL databases.
So NoSQL is going to be more flexible, usually,
but you don't have joint capabilities
and you don't have the SQL query language in general.
Okay, there can be exceptions.
And again, they will be discussed one by one.
So we have DynamoDB, we have ElastiCache,
we have Neptune, DocumentDB and Keyspaces,
and there may be new names for you, but don't worry,
we will learn about them in this section.
Then we have object store, so this is a kind of database,
yes, Amazon is free to store big objects
or Glacier to store backups and archives.
Then we have data warehousing
for SQL doing analytics with SQL
or business intelligence, BI.
So we have Redshift which is OLAP type of database,
and Athena and EMR.
We have the search type of databases.
So we have the OpenSearch type of database
to include some free text and do unstructured searches
on your data.
Graph databases, so to display relationships
between your datasets, this is Amazon Neptune.
We have ledger databases to have a list
and a ledger of transactions,
so we have the Amazon QLDB, so Quantum Ledger Database.
We have the time series types of database
for Amazon Timestream, and that's it.
We may have more database types and more databases
that it will include in section if need be, okay?
So don't worry if some of these databases
are not discussed in this section,
they will be discussed at depth in the following section
which is the data and analytics section.
Okay. So that's it for an overview.
Don't worry, you don't have to remember anything
from what I said.
It's just to give you where we're coming from.
And I will see you in the next lectures
to start discussing the databases one by one.