Amazon DynamoDB is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale. It is a fully managed cloud database and supports both document and key-value store models. Its flexible data model, reliable performance, and automatic scaling of throughput capacity, makes it a great fit for mobile, web, gaming, ad tech, IoT, and many other applications. We’ll take a look at how DynamoDB works and how it can be accelerated by DAX, the DynamoDB Accelerator. Speaker: Lex Crosett - Solutions Architect, AWS

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DynamoDB and DAX
Lex Crosett
Enterprise Solutions Architect
crosettl@amazon.com

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Characteristics of internet-scale apps
Users 1 million+
Data volume TB, PB, EB
Locality Global
Performance Milliseconds, microseconds
Request rate Millions
Access Mobile, IoT, devices
Scale Up and down
Economics Pay as you go
Developer access Instant API access

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Purpose-built databases for internet-scale apps
The world’s largest e-commerce
business, Amazon, runs on
nonrelational cloud databases
due to scale, performance, and
maintenance benefits.
— Werner Vogels
CTO, Amazon

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Amazon DynamoDB
Fully managed nonrelational database for any scale
Fast, consistent performance
Virtually unlimited throughput
Virtually unlimited storage
Encryption at rest and transit
Fine-grained access control
PCI, HIPAA, FIPS140-2 eligible
Maintenance-free
Serverless
Auto scaling
Backup and restore
Global tables

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Fully managed
Maintenance-free
Think of all the other things you could do if you didn’t have to manage:
Security
Operating system patching
Database patching
Access control
Audit
Encryption
Compliance
Durability
Sustain server, rack, and datacenter outages
Re-replicate data quickly upon hardware failure
Manage backup and restore
Availability
High availability configuration
Monitoring
Cross-region replication
Performance
Performance tuning
Indexing
In-memory caching
Scalability
Capacity planning
Host provisioning
Host repair and retirement

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No servers
No administration
AWS Lambda
integration
Fully managed
Serverless

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$$$ Savings
Automated
scaling policies
Scales up when
you need it
Scales down when
you don’t
Scheduled
auto scaling
Fully managed
Auto scaling

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Continuous backups for
point-in-time recovery
On-demand backups for
long-term data archiving
and compliance
Back up PBs of data
instantly with no
performance impact
Fully managed
Backup and restore

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Fully managed
Global tables
Build high-performance, globally
distributed applications
Low latency reads and writes
to locally available tables
Multiregion redundancy
and resiliency
Easy to set up and no application
rewrites required

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High performance
Millions of requests
per second
Trillions of items
Petabytes of storage
Single-digit millisecond
read and write latencies

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Only 3 millisecond variance
Consistent and low latency
More than 1 million requests per second
High request volume
High performance

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Fully managed, highly
available cache for DynamoDB
Even faster—
microsecond latency
Scales to millions of
requests per second
API compatible
Your applications
DAX
DynamoDB
High performance
Amazon DynamoDB Accelerator (DAX)

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Server-side encryption
for fully managed, easy
to set up table-level
encryption
Access DynamoDB
via secure Amazon
VPC endpoints
Secure
Encryption

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Fine-grained access control to
allow or deny access to items
and attributes based on the
needs of your application
AWS Identity and Access
Management (IAM) policies to
regulate access to items and
attributes stored in tables
Secure
Access control

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Customer stories

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Amazon DynamoDB
200,000+ customers

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Backup and restore on mobile app
for 300 million users
Migrated from Cassandra to
DynamoDB
• Almost 1 PB in DynamoDB, 130 million
daily API requests
• Consistent performance and 70% cost
savings (TCO)“DynamoDB provided consistent high
performance at a drastically lower cost
than Cassandra.”
—Seongkyu Kim
Samsung

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One of the 10 largest banks in the
U.S. serving 45 million customers
Migrated from mainframe to
DynamoDB:
• Serving millions of transactions with the
new serverless architecture
• Reduced latency: end-to-end requests
<55ms
• Unbound scale for app developers“New solution is so much faster...with an
average response time of 55ms.”
—Srini Uppalapati
CapitalOne

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Profile, match, and swipe data
25 TB data, 20 billion matches, 190
countries
Migrated from MongoDB to
DynamoDB
• 60% cost savings (TCO)
“DynamoDB helps us achieve greater
developer efficiency…at a lower cost.”
—Jun-young Kwak
Tinder

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“Our internal customers saw processing delays
decrease from 1 second to 100 milliseconds. It
shows how DynamoDB can serve as the foundation
of a highly efficient, mission-critical system.”
—Mike Thomas
Amazon
Every time you buy something on
Amazon.com, the internal Herd
system supports 100s of millions of
active workflows that need to start
within a couple of seconds
Migrated from Oracle
to DynamoDB:
• Workflow processing delays dropped from
1s to 100ms
• Scaling and maintenance effort dropped
10x
• Retired more than 300 Oracle hosts

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Partition Key
Mandatory
Key-value access pattern
Determines data distribution
Optional
Model 1:N relationships
Enables rich query capabilities
DynamoDB table
A1
(partition key)
A2
(sort key)
A3 A4 A7
A1
(partition key)
A2
(sort key)
A6 A4 A5
A1
(partition key)
A2
(sort key)
A1
(partition key)
A2
(sort key)
A3 A4 A5
Sort Key
Table
Items

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DynamoDB LSIs
Can only be
defined as part
of initial table
creation
A1
(partition
key)
A3
(sort key)
A2 A4 A5
A1
(partition
key)
A4
(sort key)
A2 A3 A5
A1
(partition
key)
A5
(sort key)
A2 A3 A4
• Alternate sort key
attribute
• Index is local to a
partition key
Local secondary indexes

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RCUs/WCUs
provisioned
separately for GSIs
INCLUDE A2
ALL
KEYS_ONLY
A3
(partition key)
A1
(table key)
A2 A4 A7
A3
(partition key)
A1
(table key)
A3
(partition key)
A1
(table key)
A2
• Alternate partition
(+sort) key
• Index is across all
table partition keys
• Can be added or
removed anytime
• Eventually
consistent
A3
(partition key)
A1
(table key)
A2 A4 A7
A3
(partition key)
A1
(table key)
A2
A3
(partition key)
A1
(table key)
Global secondary indexes
DynamoDB GSIs

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Data types
Type DynamoDB Type
String String
Integer, Float Number
Timestamp Number or String
Blob Binary
Boolean Bool
Null Null
List List
Set
Set of String,
Number, or Binary
Map Map

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Scaling
Throughput
Provision any amount of throughput to a table
Size
Add any number of items to a table
• Max item size is 400 KB
• Local secondary indexes (LSIs) limit the number of range keys due to
10 GB limit
Scaling
Achieved through partitioning

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Throughput
Provisioned at the table level
• Write capacity units (WCUs) are measured in 1 KB per second
• Read capacity units (RCUs) are measured in 4 KB per second
• RCUs measure strictly consistent reads
• Eventually consistent reads cost 1/2 of consistent reads
Read and write throughput limits are independent
WCURCU

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What bad NoSQL looks like…
Partition
Time
Heat

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Getting the most out of DynamoDB throughput
“To get the most out of DynamoDB
throughput, create tables where the
hash key element has a large
number of distinct values, and
values are requested fairly
uniformly, as randomly as possible.”
—DynamoDB Developer Guide
Space: access is evenly spread
over the key space
Time: requests arrive evenly
spaced in time

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Much better picture…

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25%
Requests in excess of the
soft partition limit are throttled,
after burst capacity is used up
capacity
soft limit
capacity
hard limit
Adaptive Capacity kicks in, in response to
throttling, allowing this partition to consume
unused table capacity, above the partition soft
limit
partition 1 partition 2 partition 3 partition 4

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SQL vs. NoSQL access pattern

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Hierarchical data structures as items
Use composite sort key to define a hierarchy
Highly selective result sets with sort queries
Index anything, scales to any size
Primary Key
Attributes
ProductID type
Items
1 bookID
title author genre publisher datePublished ISBN
Ringworld Larry Niven Science Fiction Ballantine Oct-70 0-345-02046-4
2 albumID
title artist genre label studio released producer
Dark Side of the Moon Pink Floyd Progressive Rock Harvest Abbey Road 3/1/73 Pink Floyd
2 albumID:trackID
title length music vocals
Speak to Me 1:30 Mason Instrumental
2 albumID:trackID
title length music vocals
Breathe 2:43 Waters, Gilmour, Wright Gilmour
2 albumID:trackID
title length music vocals
On the Run 3:30 Gilmour, Waters Instrumental
3 movieID
title genre writer producer
Idiocracy Scifi Comedy Mike Judge 20th Century Fox
3 movieID:actorID
name character image
Luke Wilson Joe Bowers img2.jpg
3 movieID:actorID
name character image
Maya Rudolph Rita img3.jpg
3 movieID:actorID
name character image
Dax Shepard Frito Pendejo img1.jpg

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… or as documents (JSON)
JSON data types (M, L, BOOL, NULL)
Document SDKs available
Indexing only by using DynamoDB Streams or AWS Lambda
400 KB maximum item size (limits hierarchical data structure)
Primary Key
Attributes
ProductID
Items
1
id title author genre publisher datePublished ISBN
bookID Ringworld Larry Niven Science Fiction Ballantine Oct-70 0-345-02046-4
2
id title artist genre Attributes
albumID
Dark Side of the
Moon
Pink Floyd Progressive Rock
{ label:"Harvest", studio: "Abbey Road", published: "3/1/73", producer: "Pink
Floyd", tracks: [{title: "Speak to Me", length: "1:30", music: "Mason", vocals:
"Instrumental"},{title: ”Breathe", length: ”2:43", music: ”Waters, Gilmour,
Wright", vocals: ”Gilmour"},{title: ”On the Run", length: “3:30", music: ”Gilmour,
Waters", vocals: "Instrumental"}]}
3
id title genre writer Attributes
movieID Idiocracy Scifi Comedy Mike Judge
{ producer: "20th Century Fox", actors: [{ name: "Luke Wilson", dob: "9/21/71",
character: "Joe Bowers", image: "img2.jpg"},{ name: "Maya Rudolph", dob:
"7/27/72", character: "Rita", image: "img1.jpg"},{ name: "Dax Shepard", dob:
"1/2/75", character: "Frito Pendejo", image: "img3.jpg"}]

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DynamoDB Streams
Partition A
Partition B
Partition C
Ordered stream of item
changes
Exactly once, strictly
ordered by key
Highly durable, scalable
24-hour retention
Sub-second latency
Compatible with Kinesis
Client Library
DynamoDB Streams
1
Shards have a lineage and
automatically close after time
or when the associated
DynamoDB partition splits
2
3
Updates
KCL
Worker
Amazon
Kinesis Client
Library
Application
KCL
Worker
KCL
Worker
GetRecords
Amazon DynamoDB
Table
DynamoDB Streams Stream
Shards

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Stream
Table
Partition 1
Partition 2
Partition 3
Partition 4
Partition 5
Table
Shard 1
Shard 2
Shard 3
Shard 4
KCL
Worker
KCL
Worker
KCL
Worker
KCL
Worker
Amazon Kinesis Client
Library application
DynamoDB
client application
Updates
DynamoDB Streams and
Amazon Kinesis Client Library

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DynamoDB Streams and AWS Lambda

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TTL job
Time-To-Live (TTL)
Amazon DynamoDB
Table
CustomerActiveOrder
OrderId: 1
CustomerId: 1
MyTTL: 1492641900
DynamoDB Streams
Amazon Kinesis
Amazon Redshift
An epoch timestamp marking when
an item can be deleted by a
background process, without
consuming any provisioned capacity
Time-To-Live
Removes data that is no longer relevant

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DynamoDB Accelerator
Amazon
DynamoDB
msμs
DAXYour App
in VPC
Amazon DynamoDB Accelerator (DAX)

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DynamoDB Accelerator (DAX)
Private IP, Client-side
Discovery
Supports AWS SDKs
Cluster based, Multi-AZ Separate Query and
Item cache

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DynamoDB in the VPC
Availability Zone #1 Availability Zone #2
Private Subnet Private Subnet
VPC endpoint
web
app
server
security
group
security
group
oMicroseconds latency in-memory cache
oMillions of requests per second
oFully managed, highly available
oRole-based access control
oNo IGW or VPC endpoint required
DAX
oDynamoDB in the VPC
oIAM resource policy
restricted
VPC Endpoints
AWS Lambda
security
group
security
group
DAX
web
app
server
DAX

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DynamoDB Global Tables
F i r s t f u l l y m a n a g e d , m u l t i - m a s t e r , m u l t i - r e g i o n d a t a b a s e
Build high performance, globally distributed applications
Low latency reads and writes to locally available tables
Disaster proof with multi-region redundancy
Easy to set up and no application re-writes required
Globally dispersed users
Replica (N. America)
Replica (Europe)
Replica (Asia)
Global App
Global Table

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Amazon DynamoDB – Backup and Restore
F i r s t N o S Q L d a t a b a s e t o a u t o m a t e o n - d e m a n d a n d c o n t i n u o u s b a c k u p s
Point in time restore
for short-term
retention and data
corruption protection
Back up hundreds of
TB instantaneously
with NO performance
impact
On-demand
backups for long-
term data archival
and compliance

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Amazon DynamoDB
E n c r y p t i o n @ r e s t
Server-side
encryption
Supports
compliance
certifications
No application
code rewrites

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Get
started
Visit DynamoDB.com