[AWS] Database

각 DB의 차이를 이해하고 구분할 줄 알아야 함

 

RDS

- Managed PostgreSQL / MySQL / Oracle / SQL Server / MariaDB / Custom
- Provisioned RDS Instance Size and EBS Volume Type & Size
- Auto-scaling capability for Storage
- Support for Read Replicas and Multi AZ
- Security through IAM, Security Groups, KMS , SSL in transit
- Automated Backup with Point in time restore feature (up to 35 days)
- Manual DB Snapshot for longer-term recovery
- Managed and Scheduled maintenance (with downtime)
- Support for IAM Authentication, integration with Secrets Manager
- RDS Custom for access to and customize the underlying instance (Oracle & SQL Server)
- Use case: Store relational datasets (RDBMS / OLTP), perform SQL queries, transactions 

 

Aurora

- Compatible API for PostgreSQL / MySQL, separation of storage and compute

- Storage: data is stored in 6 replicas, across 3 AZ – highly available, self-healing, auto-scaling 

- Compute: Cluster of DB Instance across multiple AZ, auto-scaling of Read Replicas 

- Cluster: Custom endpoints for writer and reader DB instances 

- Same security / monitoring / maintenance features as RDS 

- Know the backup & restore options for Aurora 

- Aurora Serverless – for unpredictable / intermittent workloads, no capacity planning 

- Aurora Multi-Master – for continuous writes failover (high write availability) 
- Aurora Global: up to 16 DB Read Instances in each region, < 1 second storage replication

- Aurora Machine Learning: perform ML using SageMaker & Comprehend on Aurora 

- Aurora Database Cloning: new cluster from existing one, faster than restoring a snapshot 

- Use case: same as RDS, but with less maintenance / more flexibility / more performance / more features

 

ElastiCache

- Managed Redis / Memcached (similar offering as RDS, but for caches) 

- In-memory data store, sub-millisecond latency 

- Select an ElastiCache instance type (e.g., cache.m6g.large) 

- Support for Clustering (Redis) and Multi AZ, Read Replicas (sharding) 

- Security through IAM, Security Groups, KMS, Redis Auth 

- Backup / Snapshot / Point in time restore feature 

- Managed and Scheduled maintenance 

- Requires some application code changes to be leveraged 

- Use Case: Key/Value store, Frequent reads, less writes, cache results for DB queries, store session data for websites, cannot use SQL.

 

DynamoDB

- AWS proprietary technology, managed serverless NoSQL database, millisecond latency

- Capacity modes: provisioned capacity with optional auto-scaling or on-demand capacity

- Can replace ElastiCache as a key/value store (storing session data for example, using TTL feature)

- Highly Available, Multi AZ by default, Read and Writes are decoupled, transaction capability 

- DAX cluster for read cache, microsecond read latency 

- Security, authentication and authorization is done through IAM 

- Event Processing: DynamoDB Streams to integrate with AWS Lambda, or Kinesis Data Streams 

- Global Table feature: active-active setup 

- Automated backups up to 35 days with PITR (restore to new table), or on-demand backups 

- Export to S3 without using RCU within the PITR window, import from S3 without using WCU 

- Great to rapidly evolve schemas 

- Use Case: Serverless applications development (small documents 100s KB), distributed serverless cache

 

S3

- S3 is a… key / value store for objects 

- Great for bigger objects, not so great for many small objects 

- Serverless, scales infinitely, max object size is 5 TB, versioning capability 

- Tiers: S3 Standard, S3 Infrequent Access, S3 Intelligent, S3 Glacier + lifecycle policy • Features: Versioning, Encryption, Replication, MFA-Delete, Access Logs…

- Security: IAM, Bucket Policies, ACL, Access Points, Object Lambda, CORS, Object/Vault Lock 

- Encryption: SSE-S3, SSE-KMS, SSE-C, client-side, TLS in transit, default encryption 

- Batch operations on objects using S3 Batch, listing files using S3 Inventory 

- Performance: Multi-part upload, S3 Transfer Acceleration, S3 Select 

- Automation: S3 Event Notifications (SNS, SQS, Lambda, EventBridge) 

- Use Cases: static files, key value store for big files, website hosting

 

DocumentDB

- Aurora is an “AWS-implementation” of PostgreSQL / MySQL …

- DocumentDB is the same for MongoDB (which is a NoSQL database) 

- MongoDB is used to store, query, and index JSON data 

- Similar “deployment concepts” as Aurora 

- Fully Managed, highly available with replication across 3 AZ 

- DocumentDB storage automatically grows in increments of 10GB, up to 64 TB. 

- Automatically scales to workloads with millions of requests per seconds

 

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

 

Keyspaces

- Apache Cassandra is an open-source NoSQL distributed database 

- A managed Apache Cassandra-compatible database service 

- Serverless, Scalable, highly available, fully managed by AWS 

- Automatically scale tables up/down based on the application’s traffic 

- Tables are replicated 3 times across multiple AZ 

- Using the Cassandra Query Language (CQL) 

- Single-digit millisecond latency at any scale, 1000s of requests per second

- Capacity: On-demand mode or provisioned mode with auto-scaling 

- Encryption, backup, Point-In-Time Recovery (PITR) up to 35 days 

- Use cases: store IoT devices info, time-series data, …

 

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

 

Timestream

- Fully managed, fast, scalable, serverless time series database

- Automatically scales up/down to adjust capacity

- Store and analyze trillions of events per day

- 1000s times faster & 1/10th the cost of relational databases

- Scheduled queries, multi-measure records, SQL compatibility

- Data storage tiering: recent data kept in memory and historical data kept in a cost -optimized storage

- Built -in time series analytics functions (helps you identify patterns in your data in near real-time)

- Encryption in transit and at rest

- Use cases: IoT apps, operational applications, real -time analytics, …

 

 

여러분은 온라인 트랜잭션 프로세싱(OLTP)을 수행하려 합니다. 이 작업에는 오토 스케일링 기능이 내장되어 있고, 기반 스토리지에 대해 최대 복제본 수를 제공하는 데이터베이스를 사용하고자 합니다. 이 경우, 다음 중 어떤 AWS 서비스를 추천할 수 있을까요?

- Amazon ElastiCache

- Amazon Redshift

- Amazon Aurora

- Amazon RDS

 

한 스타트업 회사가 솔루션 아키텍트인 여러분에게 사용자들이 서로 친구가 될 수 있고, 서로의 포스트에 좋아요를 남길 수 있는 소셜 미디어 웹사이트 아키텍처의 구축을 도와달라고 한 상황입니다. 이 회사는 ‘Mike의 친구들이 남긴 포스트에는 몇 개의 좋아요가 있는가?’와 같은 복잡한 쿼리를 수행하려 합니다. 이 경우, 어떤 데이터베이스의 사용을 추천할 수 있을까요?

- Amazon RDS

- Amazon Redshift

- Amazon Neptune

- Amazon ElasticSearch

 

각각의 크기가 100MB인 한 세트의 파일들이 있는데, 이 파일을 안전하고 내구성이 높은 키-값 스토어에 저장하려 합니다. 이 경우, 다음 중 어떤 AWS 서비스를 사용하는 게 권장될까요?

- Amazon Athena

- Amazon S3

- Amazon DynamoDB

- Amazon ElastiCache