# Databases & Analytics

- [Databases \& Analytics](#databases--analytics)
  - [Databases Intro](#databases-intro)
  - [Relational Databases (SQL)](#relational-databases-sql)
  - [NoSQL Databases](#nosql-databases)
    - [NoSQL data example: JSON](#nosql-data-example-json)
  - [Databases \& Shared Responsibility on AWS](#databases--shared-responsibility-on-aws)
  - [AWS RDS Overview](#aws-rds-overview)
    - [Advantage over using RDS versus deploying DB on EC2](#advantage-over-using-rds-versus-deploying-db-on-ec2)
    - [RDS Deployments](#rds-deployments)
    - [RDS Deployments: Read Replicas, Multi-AZ](#rds-deployments-read-replicas-multi-az)
    - [RDS Deployments: Multi-Region](#rds-deployments-multi-region)
  - [Amazon Aurora](#amazon-aurora)
  - [Amazon ElastiCache Overview](#amazon-elasticache-overview)
  - [DynamoDB](#dynamodb)
    - [DynamoDB Accelerator (DAX)](#dynamodb-accelerator-dax)
    - [DynamoDB Global Tables](#dynamodb-global-tables)
  - [Redshift Overview](#redshift-overview)
  - [Amazon EMR (Elastic MapReduce)](#amazon-emr-elastic-mapreduce)
  - [Amazon Athena](#amazon-athena)
  - [Amazon QuickSight](#amazon-quicksight)
  - [DocumentDB (with MongoDB Compatibility)](#documentdb-with-mongodb-compatibility)
  - [Amazon Neptune](#amazon-neptune)
  - [Amazon QLDB](#amazon-qldb)
  - [Amazon Managed Blockchain](#amazon-managed-blockchain)
  - [AWS Glue](#aws-glue)
  - [DMS - Database Migration Service](#dms---database-migration-service)
  - [Databases \& Analytics Summary](#databases--analytics-summary)

## Databases Intro

- Storing data on disk (EFS, EBS, EC2 Instance Store, S3) can have its limits
- Sometimes, you want to store data in a database…
- You can structure the data
- You build indexes to efficiently query / search through the data
- You define relationships between your datasets
- Databases are optimized for a purpose and come with different features, shapes and constraint
- **Managed Databases**: AWS takes care of maintenance, backups, and security for databases.
- **Benefits**: Reduced operational complexity, built-in high availability, disaster recovery, scalability, and enhanced security.
- **Types**:
  - **Relational Databases** (SQL)
  - **NoSQL Databases**
  - **Data Warehousing**
  - **In-memory Caching**

## Relational Databases (SQL)

- **Structured Data**: Stored in predefined schema tables, managed with SQL.
- **Use Cases**: Transactional applications, financial systems.
- **Examples**: MySQL, PostgreSQL, Oracle, SQL Server, MariaDB.

## NoSQL Databases

- **Flexible Schema**: No predefined schema, designed for fast and scalable data storage.
- **Use Cases**: Real-time applications, IoT, mobile apps.
- Benefits:
  - Flexibility: easy to evolve data model
  - Scalability: designed to scale-out by using distributed clusters
  - High-performance: optimized for a specific data model
  - Highly functional: types optimized for the data model
- **Examples**: DynamoDB, MongoDB (DocumentDB), Key-value, document, graph, in-memory, search databases

### NoSQL data example: JSON

- JSON is a common form of data that fits into a NoSQL model
- Data can be nested
- Fields can change over time
- Support for new types: arrays, etc…

```json
{
  "name": "Abc",
  "age": 30,
  "cars": [
    "Ford",
    "BMW",
    "Fiat"
  ],
  "address": {
    "type": "house",
    "number": 23,
    "street": "Abc Road"
  }
}
```

## Databases & Shared Responsibility on AWS

| **AWS Responsibility**                      | **Customer Responsibility**                      |
| ------------------------------------------- | ------------------------------------------------ |
| Infrastructure management, backups, patches | Data security, encryption, access controls (IAM) |
| Availability and failover                   | Data management, monitoring, performance tuning  |

## AWS RDS Overview

- **RDS (Relational Database Service)**: Fully managed service for relational databases.
  - It’s a managed DB service for DB use SQL as a query language.
  - Supports **MySQL**, **PostgreSQL**, **MariaDB**, **Oracle**, **SQL Server**.
  - Handles **backup**, **patching**, **high availability** (Multi-AZ), and **scaling**.

### Advantage over using RDS versus deploying DB on EC2

- RDS is a managed service:
  - Automated provisioning, OS patching
  - Continuous backups and restore to specific timestamp (Point in Time Restore)!
  - Monitoring dashboards
  - Read replicas for improved read performance
  - Multi AZ setup for DR (Disaster Recovery)
  - Maintenance windows for upgrades
  - Scaling capability (vertical and horizontal)
  - Storage backed by EBS (gp2 or io1)
- BUT you can’t SSH into your instances

### RDS Deployments

- **Read Replicas**: Improves read performance, **asynchronous** replication.
- **Multi-AZ**: Automatic failover, high availability for production environments.
- **Multi-Region**: Disaster recovery across regions, global availability.

### RDS Deployments: Read Replicas, Multi-AZ

| Read Replicas                       | Multi-AZ                                          |
| ----------------------------------- | ------------------------------------------------- |
| Scale the read workload of your DB  | Failover in case of AZ outage (high availability) |
| Can create up to 5 Read Replicas    | Data is only read/written to the main database    |
| Data is only written to the main DB | Can only have 1 other AZ as failover              |

![Read Replicas Multi-AZ](../images/read_replicas_multi_AZ.png)

### RDS Deployments: Multi-Region

- Multi-Region (Read Replicas)
  - Disaster recovery in case of region issue
  - Local performance for global reads
  - Replication cost

![Multi-Region](../images/multi_region.png)

## Amazon Aurora

- **Amazon Aurora**: High-performance RDS database.
  - Compatible with **MySQL** and **PostgreSQL**.
  - **5x faster** than MySQL, **3x faster** than PostgreSQL.
  - **Auto-scaling** storage up to **64 TB**.
  - Supports **Multi-AZ** and up to **15 read replicas**.
  - Great for **enterprise-grade** applications requiring high availability and performance.
  - Aurora costs more than RDS (20% more) – but is more efficient

## Amazon ElastiCache Overview

- **ElastiCache**: In-memory data caching service.
  - **Redis**: Advanced key-value store with replication and persistence.
  - **Memcached**: Simple, memory-only caching service.
  - Reduces database load and speeds up applications by **caching frequent queries**.
  - Caches are in-memory databases with high performance, low latency
  - AWS takes care of OS maintenance / patching, optimizations, setup, configuration, monitoring, failure recovery and backup

## DynamoDB

- Fully managed, serverless NoSQL database.
- Supports key-value and document data models.
- Automatically scales based on demand.
- Provides high availability and durability with replication across 3 AZ
- Millions of requests per seconds, trillions of row, 100s of TB of storage
- Fast and consistent in performance
- Single-digit millisecond latency – low latency retrieval
- Integrated with IAM for security, authorization and administration
- Low cost and auto scaling capabilities
- Standard & Infrequent Access (IA) Table Class

### DynamoDB Accelerator (DAX)

- In-memory caching for DynamoDB.
- **10x faster** read performance.  ingle-digit millisecond latency to microseconds latency – when accessing your DynamoDB tables
- Secure, highly scalable & highly available
- Ideal for use cases where **low-latency reads** are critical.

### DynamoDB Global Tables

- Multi-region replication for **global** applications.
- **Low-latency** reads and writes across multiple regions.
- Ensures data availability globally with **multi-master replication**.

## Redshift Overview

- Managed data warehousing service.
- Optimized for **online analytical processing (OLAP)** and big data analytics.
- Uses **columnar storage** for fast query performance.
- 10x better performance than other data warehouses, scale to PBs of data
- Columnar storage of data (instead of row based)
- Supports integration with **BI tools** (QuickSight, Tableau).
- Massively Parallel Query Execution (MPP), highly available.
- Has a SQL interface for performing the queries.
- Pay-per-query or **reserved instances** for cost savings.
- Designed for **massive datasets**.

## Amazon EMR (Elastic MapReduce)

- Managed big data processing service.
- Uses **Hadoop**, **Apache Spark**, and **Hive** for processing large data sets.
- Ideal for **data transformation**, **machine learning**, and **ETL** (Extract, Transform, Load).
- Integration with **S3**, **DynamoDB**, and **Redshift**.
- The clusters can be made of hundreds of EC2 instances
- EMR takes care of all the provisioning and configuration
- Auto-scaling and integrated with Spot instances
- Use cases: data processing, machine learning, web indexing, big data

## Amazon Athena

- Serverless query service
- Use **SQL** to query structured and unstructured data stored in **S3**.
- No infrastructure to manage, pay-per-query.
- Supports various formats like **CSV**, **JSON**, **Parquet**, and **ORC**.
- Pricing: $5.00 per TB of data scanned
- Use compressed or columnar data for cost-savings (less scan)
- Use cases: Business intelligence / analytics / reporting, analyze & query VPC Flow Logs, ELB Logs, CloudTrail trails, etc...
- Analyze data in S3 using serverless SQL, use Athena

## Amazon QuickSight

- Business Intelligence (BI) tool for data visualization.
- Serverless machine learning-powered business intelligence service to create interactive dashboards
- Fast, automatically scalable, embeddable, with per-session pricing
- Supports data from S3, Redshift, RDS, and other AWS data sources.
- **Pay-per-session** pricing model for cost efficiency.
- Use cases:
  - Business analytics
  - Building visualizations
  - Perform ad-hoc analysis
  - Get business insights using data

## DocumentDB (with MongoDB Compatibility)

- Managed document database, **MongoDB-compatible**.
- DocumentDB is the same for MongoDB (which is a NoSQL database)
- Highly scalable and durable with **Multi-AZ**.
- Built for **JSON** document storage.
- Aurora storage automatically grows in increments of 10GB, up to 64 TB.
- Automatically scales to workloads with millions of requests per seconds
- Use cases: Content management, cataloging, and mobile backends.

## Amazon Neptune

- Fully managed graph database
- A popular graph dataset would be a social network
  - Users have friends
  - Posts have comments
  - Comments have likes from users
  - Users share and like posts…
- Highly available across 3 AZ, with up to 15 read replicas
- Build and run applications working with highly connected datasets – optimized for these complex and hard queries
- Can store up to billions of relations and query the graph with milliseconds latency
- Highly available with replications across multiple AZs
- Great for knowledge graphs (Wikipedia), fraud detection, recommendation engines, social networking

## Amazon QLDB

- QLDB stands for ”Quantum Ledger Database”
- A ledger is a book **recording financial transactions**
- Fully Managed, Serverless, High available, Replication across 3 AZ
- Used to **review history of all the changes made to your application data** over time
- **Immutable** system: no entry can be removed or modified, cryptographically verifiable
- 2-3x better performance than common ledger blockchain frameworks, manipulate data using SQL
- Difference with Amazon Managed Blockchain: no decentralization component, in accordance with financial regulation rules

## Amazon Managed Blockchain

- Blockchain makes it possible to build applications where multiple parties can execute transactions without the need for a trusted, central authority.
- Amazon Managed Blockchain is a managed service to:
  - Join public blockchain networks
  - Or create your own scalable private network
- Compatible with the frameworks Hyperledger Fabric & Ethereum

## AWS Glue

- Managed extract, transform, and load (ETL) service
- Useful to prepare and transform data for analytics
- Fully serverless service
- Glue Data Catalog: catalog of datasets
  - can be used by Athena, Redshift, EMR

## DMS - Database Migration Service

- Quickly and securely migrate databases to AWS, resilient, self healing
- The source database remains available during the migration
- Supports:
  - Homogeneous migrations: ex Oracle to Oracle
  - Heterogeneous migrations: ex Microsoft SQL Server to Aurora

## Databases & Analytics Summary

- Relational Databases - OLTP: RDS & Aurora (SQL)
- Differences between Multi-AZ, Read Replicas, Multi-Region
- In-memory Database: ElastiCache
- Key/Value Database: DynamoDB (serverless) & DAX (cache for DynamoDB)
- Warehouse - OLAP: Redshift (SQL)
- Hadoop Cluster: EMR
- Athena: query data on Amazon S3 (serverless & SQL)
- QuickSight: dashboards on your data (serverless)
- DocumentDB: “Aurora for MongoDB” (JSON – NoSQL database)
- Amazon QLDB: Financial Transactions Ledger (immutable journal, cryptographically verifiable)
- Amazon Managed Blockchain: managed Hyperledger Fabric & Ethereum blockchains
- Glue: Managed ETL (Extract Transform Load) and Data Catalog service
- Database Migration: DMS
- Neptune: graph database