Turbocharge Purpose Built Databases with Amazon Elasticache Improve Application Performance with In-Memory Data Stores

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Turbocharge purpose built databases with Amazon ElastiCache Improve application performance with in-memory data stores

Japan Purpose Built Database Week

Tom Kuehle Amazon ElastiCache GTM Specialist

Modern applications and How ElastiCache Upcoming ElastiCache the need for purpose- enhances purpose-built features that will enhance built databases application performance performance, security, and reliability

Explosion of data Micro-services changing data Applications require global and application requirements scale and rapid response

Speed Scale

Data grows 10x every 5 Growing need for multiple Time-to-insights and actions years driven by network databases and data models in milliseconds at Internet connected smart devices within the same application scale

Using microservices over monolithic applications

Architect services Select from a portfolio Use Amazon ElastiCache in- Innovate faster through ground-up for the of purpose-built memory database to managed services explosion of data, cloud services, optimized improve the performance of workload migration, and to your application purpose built databases and using micro services requirements analytics solutions

• Database caching • Real time data processing • Versatile data models • Workload off-loading

Unstructured/ High Variety Amazon Amazon S3 Glacier Amazon ElastiCache Amazon Amazon DocumentDB DynamoDB and DAX Amazon Keyspaces Amazon CloudSearch and Data Sources Elasticsearch Amazon Service RDS & Amazon Structured/ Redshift Low Variety

High Low Request Rate (Velocity) Low High Latency (Response time)

ElastiCache + RDS “Query response time has become the most ElastiCache + Aurora important DB metric” ElastiCache + Redshift ScaleGrid, March 2019 ElastiCache + Neptune ElastiCache + DynamoDB ElastiCache + DocumentDB ElastiCache + S3/object stores ElastiCache + …. better together!

© 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Turbocharge real-time applications Critical component to optimizing user experiences • retrieving data from optimized databases often falls short of modern, real-time application requirements. • add ElastiCache to your end-to-end architecture.

Use ElastiCache when:

• Seeing frequent identical queries • Experiencing high latency on reads • Requiring sub-millisecond performance to render reads • Looking for cost efficiencies from high I/O due to heavy reads

Database Proxy EC2 Tier Amazon RDS, Aurora, Redshift Database ApplicationApplicatio n Proxy*

• Eliminate duplicate queries • Reduce relational workloads • Improve end-user response times • No application code changes • Cost neutral or likely cost savings Amazon ElastiCache

* DB proxy available through AWS © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved. partners or built with code refactoring Duolingo uses AWS databases to serve up over 31 billion items for 80 language courses with high performance and scalability

Primary database: Amazon DynamoDB • 24,000 reads and 3,000 writes per second • Personalize lessons for users taking 6bn exercises per month

In-memory caching: Amazon ElastiCache • Instance access to common words and phrases

Transactional data: Amazon Aurora • Maintain user data

Challenges Average response time of the API layer is <40ms. Redis was introduced to for real time processing of 4 million daily bookings. Tried running Redis on EC2, but time consuming, error prone, and expensive.

Solution Using both RDS and Amazon ElastiCache in multi-AZ allowed them to outsource all the management to AWS. ElastiCache as a caching layer on RDS MySQL provides sub-millisecond latency even in times of peak traffic of hundreds of© 2020, thousands Amazon Web Services, of cabInc. or itsrequests Affiliates. All rights per reserved. minute. Drive faster time-to-insights Use ElastiCache within your end-to-end data analytics architectures

Retrospective analysis and ElastiCache drives fast, real-time processing of large data analytics volumes Actions reporting

Operational Visualizations Data Interactive Big Data Real time Recommendations Predictive Analytics Warehousing Query Processing Analytics Analytics

Time-to-insight performance Data ingestion (e.g., mobile, IoT)

Real-time edge analytics (e.g., consumer services, security, AdTech)

Machine learning (e.g., inferences, pattern detection, recommendations)

AWS Lambda Amazon Kinesis

Amazon EMR Amazon Amazon Managed ElastiCache Amazon Streaming for Redis RDS for Kafka Amazon EC2

Data Data Data Buffer fast- Load Sources Streams Transformation moving data in-memory

Real-time stream processing: Amazon ElastiCache • Multi-stream union and self-join • 24-hour look-back window

Transactional data: Amazon Aurora • Operational queries

Data warehousing: Amazon Redshift • Analytical queries

1 2 3 The Future is Purpose Modern Applications Amazon ElastiCache is a Built have a Need for Speed Critical Component

Data volume growth is explosive, and data analysis drives competitive Modern data-driven apps need low In-memory caching to improve advantage latency response times database response times and ------workload throughput Micro service architectures provide Data pipelines need fast ingest, --- developers the right tools for the throughput, and analysis Multitude of key-value data models right job --- for real-time processing --- Trends in IoT, ML, edge, 5G and real- --- The era of monolithic applications is time services are accelerating velocity Most any applications can benefit over from faster response times

The features we are sharing are not a commitment to deliver in 2020. Unless already launched, they simply provide general guidance on product direction and priorities.

Please contact your local AWS account team if you desire greater detail. Under a nondisclosure agreement (NDA) we will be able to share more confidential information.

Also note this is just a sample of 2020 features. There are many more product enhancements outside of what is being discussed today.

Ø Performance: cluster sizes, available memory, CPU horsepower Ø Open source: version concurrency, community contributions Ø Security/authorization: role-based access control, consistent IAM Ø HA/DR: cross region replication, cluster mode migrations Ø Data proximity: moving data processing closer to the end consumer Ø Data persistence: reducing or eliminating in-memory data loss

Secondary (Passive) Region Read

Primary (active) region Read/Write

Secondary (Passive) Region Read

Benefits • Client-side caching OSS code, snapshot, and throughput improvements. • Better authentication and authorization for Redis removing an important roadblock for adoption by customers • Bring the power of Redis 6.0 to a fully managed service that’s well integrated with AWS infrastructure and services.

Benefits • Data residency in your city/state/country boundary. • Reduce latency using close to the user deployments with seamless access to other AWS services.