Databases Flashcards
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
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
Amazon QuickSight
- Serverless machine learning-powered business intelligence service to
create interactive dashboards - Fast, automatically scalable, embeddable, with per-session pricing
- Use cases:
- Business analytics
- Building visualizations
- Perform ad-hoc analysis
- Get business insights using data
- Integrated with RDS, Aurora, Athena, Redshift, S3…
Amazon Athena
Serverless query service to analyze data stored in Amazon S3
* Uses standard SQL language to query the files
* Supports CSV, JSON, ORC, Avro, and Parquet (built on Presto)
* 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…
* Exam Tip: analyze data in S3 using serverless SQL, use Athena
Amazon EMR
(Elastic MapReduce)
- EMR stands for “Elastic MapReduce”
- EMR helps creating Hadoop clusters (Big Data) to analyze and process vast amount of data
- The clusters can be made of hundreds of EC2 instances
- Also supports Apache Spark, HBase, Presto, Flink…
- 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…
Redshift
- Redshift is based on PostgreSQL, but it’s not used for OLTP
- 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, scale to PBs of data
- Columnar storage of data (instead of row based)
- Massively Parallel Query Execution (MPP), highly available
- Pay as you go based on the instances provisioned
- Has a SQL interface for performing the queries
- BI tools such as AWS Quicksight or Tableau integrate with it
DynamoDB
- Fully Managed Highly available with replication across 3 AZ
- NoSQL database - not a relational database
- Scales to massive workloads, distributed “serverless” database
- 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
* Fully Managed in-memory cache for DynamoDB
* 10x performance improvement – single- digit millisecond latency to microseconds latency – when accessing your DynamoDB tables
* Secure, highly scalable & highly available
* Difference with ElastiCache at the CCP level: DAX is only used for and is integrated with DynamoDB, while ElastiCache can be used for other databases applications table Amazon
DynamoDB – Global Tables
* Make a DynamoDB table accessible with low latency in multiple-regions
* Active-Active replication (read/write to any AWS Region)
Amazon Aurora
- Aurora is a proprietary technology from AWS (not open sourced)
- OLTP database
- PostgreSQL and MySQL are both supported as Aurora DB
- Aurora is “AWS cloud optimized” and claims 5x performance improvement over MySQL on RDS, over 3x the performance of Postgres on RDS
- Aurora storage automatically grows in increments of 10GB, up to 128 TB
- Aurora costs more than RDS (20% more) – but is more efficient
- Not in the free tier
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
