[AWS Practice] 10. RDS

Sunwu Park·2024년 3월 2일
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AWS-Study

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• It’s a managed DB service for DB use SQL as a query language.

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

Amazon Aurora

  • AWS cloud optimized” and claims 5x performance improvement over MySQL on RDS, over 3x the performance of Postgres on RDS
  • Aurora costs more than RDS (20% more) but is more efficient

Amazon Aurora Serverless

  • Automated database instantiation and auto-scaling based on actual usage
  • Use cases: good for infrequent, intermittent or unpredictable workloads...

RDS Deployments: Read Replicas, Multi-AZ

RDS Deployments: Multi-Region

  • Disaster recovery
  • Local performance for global reads
  • But, Replication cost

ElastiCache

DynamoDB

  • NoSQL Database
  • Serverless Database
  • Fast and consistent in performance
  • Single-digit millisecond latency - low latency retrieval

DynamoDB Accelerator - DAX

  • Fully Managed in-memory cache for DynamoDB
  • 10x performance improvement
  • Secure, highly scalable & highly available
  • Only for DynamoDB / ElastiCache can be used for other databases


=> cannot join other table

Global Tables

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


=> read/write access to any region of AWS on this global table, makes it an active-active replication because you can actively write to any region and it will actively be replicated into other regions.

RedShift

  • Redshift is based on PostgreSQL
  • OLAP - Online Analytical Processing(analytics and data warehousing)
  • Load data once every hour
  • Columnar storage of data (not row based)
  • Massively Parallel Query Execution (MPP), highly availble
    => computation quickly
  • BI tools such as AWS Quicksight or Tableau integrate with it

RedShift Serverless

  • Automatically provisions and scales data warehouse underlying capacity
  • Run analytics workloads without managing data warehouse infrastructure
  • Pay only for what you use (save costs)
  • Use cases: Reporting, dashboarding applications, real-time analytics

Amazon EMR

  • Elastic MapReduce
  • helps creating Hadoop clusters(Big Data) -> analyze and process vast amount of data
  • takes care of all the provisioning and configuration
  • Use cases: data processing, machine learning, web indexing, big data...

Amazon Athena

  • Serverless query service to analyze data stored in Amazon S3
  • Use SQL Language
  • SupportsCSV,JSON,ORC,Avro,andParquet(builtonPresto
  • Use cases: Business intelligence / analytics / reporting, analyze &
    query VPC Flow Logs, ELB Logs, CloudTrail trails, etc...

[Exam Tip: analyze data in S3 using serverless SQL, use Athena]

Amazon QuickSight

  • Serverless machine learning-powered business intelligence service to create interactive dashboards
  • Use cases:
    • Business analytics
    • Building visualizations
    • Perform ad-hoc analysis
    • Get business insights using data

DocumentDB

  • DocumentDB is the same for MongoDB (which is a NoSQL database)
    => to store, query, and index JSON data
  • Fully Managed, highly available with replication across 3 AZ

Amazon Neptune

  • Fully managed graph database
  • A popular graph dataset would be a social network
  • Highly available across 3 AZ, with up to 15 read replicas
  • Great for knowledge graphs (Wikipedia), fraud detection,
    recommendation engines, social networking

Amazon TimeStream

  • Fully managed, fast, scalable, serverless time
    series database
  • Automatically scales up/down to adjust capacity
  • 1000s times faster & 1/10th the cost of
    relational databases

Amazon QLDB

  • QLDB stands for ”Quantum Ledger Database”
  • A ledger is a book recording financial transactions
  • FullyManaged,Serverless,Highavailable,Replicationacross3AZ
  • review history of all the changes made to your application data
  • 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

  • multiple parties can execute transactions without the need for a trusted, central authority.
  • join public blockchain networks
  • create own scalable private network
  • Hyperledger Fabric, Ethereum

AWS Glue

  • Managed extract, transform, and load (ETL) service
  • prepare and transform data for analytics
  • serverless
  • Glue Data Catalog: is a catalog of your datasets in your Alias infrastructure => alert reference of everything, the column names, the field names, the field types, et cetera, et cetera. => Redshift

DMS(Database Migration Service)

  • Quickly and securely migrate databases to AWS, resilient, self healing

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