Accelerating DynamoDB with DAX

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Amazon DynamoDB Accelerator (DAX)
DynamoDB Just Got Faster

6/14/2017 Slides not intended for redistribution 2
Amazon DynamoDB
Fast and flexible NoSQL database
service for any scale

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DynamoDB Customers
Ad TechGaming IoTMobile Web

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Scalability Performance Security Availability Manageability Developer
Platform

Performance
Scalability Performance Security Availability & Data Protection Manageability Development Platform

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DynamoDB: consistent performance at scale
ConsistentSingle-Digit Millisecond Latency
Requests(millions)
Latency(milliseconds)
“We cannot afford to waste a 3 or 4 milliseconds...”
“We have 20ms to make a decision… ”

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DynamoDB
Cache
Your Applications
Traditional side cache
DynamoDB
Your Applications
Caching made simple
DynamoDB Accelerator

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Milliseconds to
microseconds

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• Fully managed, highly available: handles all software management,
fault tolerant, replication across multi-AZs within a region
• DynamoDB API compatible: seamlessly caches DynamoDB API
calls, no application re-writes required
• Write-through: DAX handles caching for writes
• Flexible: Configure DAX for one table or many
• Scalable: scales-out to any workload with up to 10 read replicas
• Manageability: fully integrated AWS service: Amazon CloudWatch,
Tagging for DynamoDB, AWS Console
• Security: Amazon VPC, AWS IAM, AWS CloudTrail, AWS
Organizations
Features
DynamoDB Accelerator (DAX)
DynamoDB
Your Applications

Fully managed, highly available

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High Availability
AMAZON VPC
EC2
App
DAX
SDK
DynamoDB
AZ1
AZ2
AZ3

DynamoDB API compatible

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Q: How easy is it to add in-
memory caching with DAX?
A: Comment out the this code
and add this code

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• Read APIs: GetItem, BatchGetItem, Query, Scan
• Modify APIs: PutItem, UpdateItem, DeleteItem,
BatchWriteItem
• Control plane APIs: Not supported (CreateTable,
DeleteTable, etc.)
DAX is API compatible with DynamoDB

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DAX has two caches
Query Cache {query, scan}
Item Cache {GetItem, PutItem}
key, value
query text, result set

Write-through

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DynamoDB Accelerator (DAX): Reads
DynamoDB
Your Applications
t=1 GetItem
t=2 Cache Miss
t=3 GetItem
t=4 Populate cache
t=5 Return item

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DynamoDB Accelerator (DAX): Reads
DynamoDB
Your Applications
t=1 GetItem
t=2 Cache Hit
t=3 Return item

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DynamoDB Accelerator (DAX): Write-through
DynamoDB
Your Applications
t=1 PutItem
t=2 Write
t=3 Populate cache
t=4 Return item

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DynamoDB Accelerator (DAX): Read after Write
DynamoDB
Your Applications
t=1 GetItem
t=2 Cache Hit
t=3 Return item

Flexible

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DynamoDB Accelerator (DAX): Flexible
DynamoDB
Your Application
Table #1
DynamoDB
Your Application
Table #1
Table #2
DynamoDB
Your Applications
Table #1
DynamoDB
Your Applications
Table #1
Table #2
One-to-One One-to-Many Many-to-One Many-to-Many

Scalable

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Scaling DAX
. . .
Scale Up
(15.25 GiB to 244 GiB)
Scale-out
Scale Out
(up to 10 replicas)
Scale-up
. . .

Manageability

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Amazon
CloudWatch
AWS Management
Console
Cost-based
Tagging

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Cache Eviction
Time-to-live (TTL) Least Recently Used
(LRU)
Write-through
eviction

Security

VPC subnet IAM
AWS
CloudTrail

Customer scenarios

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Customer Use Case #1: Unpredictable spikes

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Customer Use Case #2: Speed
Response times in microseconds

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Customer Use Cases
DynamoDB
App
DAX
DynamoDB
App
DynamoDB
App
Write-Through Cache
Write-Around Cache
Write-Back Cache
(not available today)
1 2
34
1 3
42
1
23
DAX
DAX

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Repeated users are now being handled by the DAX cache
without making the more expensive (in both latency & cost)
call to DynamoDB
Shahar Kobrinky
VP of Architecture and Scale at Eyeview
“
”
DAX represents a big opportunity for us to
find the optimal balance between infrastructure cost and
system performance
Brandon O’Brien
Principle Software Engineer, Expedia, Inc.
“
”

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The AWS team has taken a best-practice architectural
pattern and turned it into something repeatable and
valuable for its customers
Glenn Nethercutt
Chief Architect, Genesys
“
”
The ability to supercharge DynamoDB with DAX is
something we're looking forward to
Pat Malatack
General Manager of Twilio Messaging
“
”

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Key Benefits
• Fast performance: Microseconds response
times at millions of reads/sec from single DAX
cluster
• Ease of use: DynamoDB API compatible -
requires minimal code change for existing
applications, simplifying developer experience
• Lower costs: Reduce provisioned read
capacity for DynamoDB tables for tables with
hot data
DynamoDB Accelerator (DAX) In public preview
DynamoDB
Your Applications

FAQs

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Q: Does DAX invalidate query result sets
with puts, updates or deletes?
Scenario:
t=1 Query
t=2 PutItem
t=3 Query

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Q: How does DAX handle strongly
consistent reads?

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Q: Does DAX help with hot-keys?

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Q: What are the current limitations?
• Java SDK only
• Regions: N. Virginia, Oregon, Ireland
• Instances: r3

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