Databases

Relational Databases #

A relational database is a type of database that organizes data into rows and columns, which collectively form a table where the data points are related to each other.

Data is typically structured across multiple tables, which can be joined together via a primary key or a foreign key. These unique identifiers demonstrate the different relationships which exist between tables, and these relationships are usually illustrated through different types of data models.

No-SQL Databases #

• No-SQL = non-relational databases
• No-SQL databases are purpose built for specific data models and have flexible schemas for building modern applications

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)

Use cases: Key-value, document, graph, in-memory, search datamases

RDS and Aurora #

Amazon RDS #

RDS stands for Relational Database Service. It is a managed DB service.

It allows creating databases in the cloud that are managed by AWS:

• Postgres
• MySQL
• MariaDB
• Oracle
• Microsoft SQL Server
• IBM DB2
• Aurora (AWS Proprietary)

Advantage of using RDS vs deploying DB on EC2:

• RDS is a managed service
  • Automated Provisioning and 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
  • Maintenance windows for upgrades
  • Scaling capability (both, vertical and horizontal)
  • Storage backed by EBS
• Not possible to SSH into DB instances (managed service)

Example RDS application architecture #

Amazon Aurora #

• Aurora is proprietary technology from AWS (not open sourced)
• PostgreSQL and MySQL are both supported
• Aurora is “AWS Optimized” and claims to be 5x performance improved over MySQL on RDS and 3x the performance of Postgres on RDS
• Aurora storage automatically grows and increments of 10GB (up to 128 TB)
• Aurora costs about 20% more than RDS

Amazon Aurora Serverless #

• Automated (on-demand) database with autoscaling based on actual usage
• PostgreSQL and MySQL are both supported as Aurora Serverless DB
• No capacity planning required
• Least management overhead
• Pay-per-second, COULD BE more effective

Use cases: infrequent, intermittent or unpredictable workloads.

Aurora with no management overhead = Aurora Serverless. #

Create RDS database #

Aurora and RDS > Create a database

RDS Deployment options #

• Read Replicas
  • Scale the read workload of your DB
  • Can create up to 15 replicas
  • Data is only written to the main DB
• Multi-AZ
  • Failover in case of AZ outage (High-Availability)
  • Data only read/written to the main DB
  • Can only have 1 AZ as a failover
• Multi-Region
  • Multi-Region (Read Replicas)
  • Writes only to the main database
  • Local performance for global reads
  • Additional replication cost
  • Use case: DR in another region

Other Database Types #

Amazon ElastiCache #

• The same way RDS is to get managed Relational Databases, ElastiCache is to get managed Redis or Memcached.

• Caches are in-memory databases with high performance and low latency

• Helps reducing load from databases with read-intensive workloads

• AWS taking care of OS maintenance, patching, optimizations, setup, configuration, monitoring, failure recovery and backups

More: https://docs.aws.amazon.com/elasticache/

DynamoDB #

• Fully managed, Highly Available with replication across 3AZ
• No-SQL database - not a relational DB
• Scales to massive workloads, distributed, “serverless”
• Millions of requests per second, trillions of row, 100s TB of storage
• Fast and consistent performance
• Single-digit millisecond latency
• Integrated with IAM for security, authorization and administration
• Low cost and auto scaling capabilities
• Standard & Infrequent Access (IA) Table Class

DynamoDB Accelerator (DAX) #

• Fully Managed in-memory cache for DynamoDB
• 10x performance improvement when accessing DynamoDB tables

DAX is only used for DynamoDB where Elasticache can be used for other databases.

DynamoDB Global Tables #

• Makes DynamoDB table accessible with low latency in multiple-regions
• Active-Active replication (read/write to any AWS Region)

Redshift #

• Redshift is based on PostgreSQL
• It’s OLAP - Online Analytical Processing (analytics and data warehousing)
• Load data once every hour, not every second
• 10x better performance than other data warehouses
• Scales to PBs of data
• Columnar storage of data (instead of rows)
• Massively Parallel Query Execution (MPP)
• Pay-as-you-go based on the instances provisioned
• Has a SQL interface for performing queries

Redshift Serverless #

• Auto Scaling
• Run analytics workload without managing data warehouse infrastructure
• Pay only for what you use
• Use cases: Reporting, real-time analytics

Amazon EMR #

• EMR stands for “Elastic MapReduce”
• EMR helps creating Hadoop clusters (Big Data) to analyze and process vast amounts of data
• 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

Athena #

• Serverless query service to perform analytics against S3 objects
• Uses standard SQL language to query the files
• Supports CSV, JSON, ORD, Avro, Parquet
• Pricing: $5 per TB of data scanned
• Use cases: Business intelligence, analytics, reporting, analyze & query VPC Flow Logs, ELB Logs, CloudTrail logs, etc.

Exam tip: analyze data in S3 using serverless SQL = Athena #

QuickSight #

Allows creating dashboards for services used in AWS. Per-session pricing.

• Serverless machine-learning powered business intelligence service to create interactive dashboards
• Use cases:
  • Business analytics
  • Building visualisations
  • Ad-hoc analysis
  • Get business insights using data
• Integrated with RDS, Aurora, Athena, Redshift, S3

More: https://docs.aws.amazon.com/quicksight/

DocumentDB #

Aurora version for MongoDB (NoSQL database).

• MongoDB is used to store, query and index JSON data
• Fully Managed, Highly Available with replication across 3AZ
• DocumentDB storage automatically grows in increments of 10 GB

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 3AZ with up to 15 replicas
• Build and run applications working with highly connected datasets = optimized for those complex queries
• Can store up to billions of relations and query the graph with milliseconds latency
• Use cases: knowledge graphs (Wikipedia), fraud detection, recommendation engines, social networking

Amazon Timestream #

• Serverless time series database
• Automatically scales up and down to adjust capacity
• Store and analyze trillions of events per day

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 that allows:
  • Join public Blockchain networks
  • Create your own scalable, private network
• Compatible with:
  • Hyperledger Fabric
  • Ethereum

AWS Glue #

Managed Extract, Transform and Load (ETL) service.

• Useful to prepare and transform data for analytics
• Fully serverless service

DMS #

DMS - Database Migration Service

• Quick and secure migrate databases to AWS

• The source database remains available during the migration

• Homogeneous migrations: i.e. Oracle to Oracle

• Heterogeneous migrations: i.e. MSSQL to Aurora

Database 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
• Timestream: time-series database

» Sources « #

• Amazon RDS and Aurora Documentation: https://docs.aws.amazon.com/rds/
• ElastiCache: https://docs.aws.amazon.com/elasticache/
• QuickSight: https://docs.aws.amazon.com/quicksight/

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