Database

• Database is a data-store that stores semi-structured and structured data.
• Database is more complex data stores because it required using formal design and modeling techniques.
• Relational Database is a structured data that strongly represents tabular data (tables, rows and columns).
• Non-relational database are semi-structured data that may or may not distantly resemble tabular data.
• A database infers someone is using a relational row-oriented data store.
• Data Warehouse is a relational datastore designed for analytic workloads, which is generally column-oriented data-store.
• Companies will have terabytes and millions of rows of data and they need a fast way to be able to produce analytics reports.
• Data Warehouses perform aggregation.
• Aggregation is the idea of grouping data like finding a total or average for a set of data.
• Hot means they can return queries very fast even though they have vast amounts of data.
• Data warehouses are infrequently accessed, meaning they aren't intended for real-time reporting.
• Data Warehoused needs to consume data from a relational database.
• Key-Value Store is a database type of non-relational database (NoSQL) that uses a simple key-value method to store data.
• A key-value stores a unique key alongside a value.
• Key-value stores are dumb and fast but lack relationship, indexes and aggregation.
• A document store is a NoSQL database that stores documents as its primary data structure.
• A document in document store could be an XML, JSON or JSON-like.
• NoSQL Database Services:

  1. DynamoDB
  2. DocumentDB
  3. Amazon KeySpaces
• DynamoDB is an AWS serverless NoSQL key-value and document database.
• DynamoDB is designed to scale to billions of records with guaranteed consistent data return in at least a second.
• DynamoDB is AWS's flagship database service.
• When we want a massively scalable database we think of DynamoDB.
• DocumentDB is a NoSQL document database that is "MongoDB compatible".
• When you want a MongoDB database you will use DocumentDB.
• Amazon Keyspaces is a fully managed Apache Cassandra database.
• When you want to use Apache Cassandra you will use Amazon Keyspaces.
• Relational Database Services:

  1. Relational Database Service (RDS)
  2. Aurora
  3. Aurora Serverless
  4. RD3 on VMWare
• Relational Database Service (RDS) is a relational database service that supports multiple SQL engines.
• Relational Databases are the most commonly used type of database among tech companies and start-ups.
• Relational Database Service support the following SQL Engines:

  1. MySQL
  2. MariaDB
  3. Postgres
  4. Oracle
  5. Aurora
  6. Microsoft SQL Server
• Aurora is a fully managed database of either MySQL and PSQL database.
• When you want a highly available, durable, scalable relational database or MySQL or PSQL you use Aurora.
• Aurora Serverless is the serverless on-demand version of Aurora.
• When you want the most benefits of Aurora but can trade to have cold-starts or you don't have lots of traffic demand, you use Aurora Serverless.
• RD3 on VMware allows you to deploy RD3 supported engines to an on-premise data-center.
• When you want a database managed by RDS on your own datacenter, you use RD3 onVMware.
• Redshift is a petabyte-size data-warehouse.
• When you want to quickly generate analytics or reports from a large amount of data, you use Redshift.
• ElastiCache is a managed database of the in-memory and caching open-source databases.
• When you need to improve the performance of application by adding a caching layer in-front of web-server or database., you use ElastiCache.