Databases in AWS

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Hello, my name is Demetria Crawford and in this lesson we will discuss AWS Cloud database systems. When we look at databases, we have to have an understanding of what we're using the database for, what type of data are we collecting, and how are we going to use that data. That will help us to determine the schematics of our database. What type of structure do we wanna have? There are several database types that we use and with each type there are various AWS services that are available that meet that database type. For example, a very common database type is relational databases. With relational databases, we have tables and row that we are able to actually have a structure to to query the data from. We often use Microsoft SQL for something like this or MySQL, and within AWS services we have Amazon RDS, we could use Redshift or Aurora. And even with those choices we have options that we're able to select as far as how we're going to use the data. The amount of data that we're going to store in our database will help make a difference. For example, if we have a data warehouse, how we manage our database may be a little bit different and we may not want a structured database such as RDS for that type of data. Next, we also wanna know is this going to be a managed database? Will AWS manage the database, meaning applying upgrades to the operating system and the database software that's being used or will that be managed by the actual customer? All of these are factors that we have to take in to decide which service works best for us from AWS. So some of the other database types we may use is key-valued. We see this with NoSQL databases. These are databases that don't have the structure that we see with relational databases. And then there are options we have available that isn't specifically a database, but works alongside with databases to make the performance better. And that's what our in-memory databases are or in-memory services that are used to cache information that may be queried on a regular basis from a database so that it doesn't have to perform as many queries. And the database is readily available from the requester. We can have a document or content management type storage that we have available as a form of a database such as MongoDB or DocumentDB in this case. Then there's wide column that we will use Amazon Key Spaces for high-scale industrial apps. We have graphs that we may use in Amazon Neptune. Time series where we may use this type of database for Internet of Things or IoT applications or for DevOp type of applications, we would use Amazon Time Stream. And then there's Ledger where we record or there's a systems of records that we may use with like a supply chain or registrations. And in this case, we have Amazon Ledger Database services. Stay tuned for the next lesson where we will review AWS RDS. Thanks for watching.