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Introduction to Amazon DynamoDB
Sean Shriver
NoSQL Solutions Architect
AWS Solution Architecture
15 March 2017
Agenda
• Brief history of data processing
• Relational (SQL) vs. nonrelational (NoSQL)
• NoSQL solutions on AWS
• Amazon DynamoDB’s fully managed features
• Demo – serverless applications
Data volume since 2010
• 90% of stored data generated in
last 2 years
• 1 terabyte of data in 2010 equals
6.5 petabytes today
• Linear correlation between data
pressure and technical innovation
• No reason these trends will not
continue over time
Timeline of database technology
DataPressure
Technology adoption and the hype curve
Relational (SQL) vs.
nonrelational (NoSQL)
Relational vs. nonrelational databases
Traditional SQL NoSQL
DB
Primary Secondary
Scale up
DB
DB
DBDB
DB DB
Scale out
SQL (Relational)
Price Desc.
$11.50
$8.99
Chaplin’s
first …
Columns
Rows
Primary Key Index
$14.95
One of 2
major …
The
Partitas
Product
ID
Type
1
2
3
Products
Book
Album
Movie
SQL (Relational)
Price Desc.
$11.50
$8.99
Chaplin’s
first …
Columns
Rows
Primary Key Index
$14.95
One of 2
major …
The
Partitas
Product
ID
Type
1
2
3
Products
Book
Album
Movie
Books
Title Date
Odyssey 1871
Book ID
1
Books
Author
Homer
SQL (Relational)
Price Desc.
$11.50
$8.99
Chaplin’s
first …
Columns
Rows
Primary Key Index
$14.95
One of 2
major …
The
Partitas
Product
ID
Type
1
2
3
Products
Book
Album
Movie
Books
Title Date
Odyssey 1871
Book ID
1
Books
Genre Director
Drama,
Comedy
Chaplin
Movie ID Title
3 The Kid
Movies
Author
Homer
SQL (Relational)
Products
Price Desc.
$11.50
$8.99
Chaplin’s
first …
Columns
Rows
Primary Key Index
$14.95
One of 2
major …
The
Partitas
Product
ID
Type
1
2
3
Book
Album
Movie
Books Albums
Title Date
Odyssey 1871
Book ID
1
Books Albums
Title
6 Partitas
Album
ID
Artist
2
Genre Director
Drama,
Comedy
Chaplin
Movie ID Title
3 The Kid
Movies
Bach
Author
Homer
SQL (Relational)
Price Desc.
$11.50
$8.99
Chaplin’s
first …
Columns
Rows
Primary Key Index
$14.95
One of 2
major …
The
Partitas
Product
ID
Type
1
2
3
Books Albums
Products
Book
Album
Movie
Title Date
Odyssey 1871
Book ID
1
Books Albums
Title
6 Partitas
Album
ID
Artist
2
Genre Director
Drama,
Comedy
Chaplin
Movie ID Title
3 The Kid
Movies Tracks
Track
Partita
No. 1
Album
ID
Track ID
2 1
Bach
Author
Homer
SQL (Relational) vs. NoSQL (Non-relational)
Product
ID
Type
Odyssey Homer1 Book ID
2 Album ID 6 Partitas
2
Album ID:
Track ID
Partita
No. 1
Bach
Attributes
Schema is defined per item
Items
Partition Key Sort Key
3 Movie ID The Kid
Drama,
Comedy
1871
Chaplin
Primary Key Products
Price Desc.
$11.50
$8.99
Chaplin’s
first …
Columns
Rows
Primary Key Index
$14.95
One of 2
major …
The
Partitas
Product
ID
Type
1
2
3
Title Date
Odyssey 1871
Book ID
1
Books Albums
Title
6 Partitas
Album
ID
Artist
2
Genre Director
Drama,
Comedy
Chaplin
Movie ID Title
3 The Kid
Movies
Products
Book
Album
Movie
Tracks
Track
Partita
No. 1
Album
ID
Track ID
2 1
Author
Homer Bach NoSQL design optimizes for
compute instead of storage
Why NoSQL?
Optimized for storage Optimized for compute
Normalized/relational Denormalized/hierarchical
Ad hoc queries Instantiated views
Scale vertically Scale horizontally
Good for OLAP Built for OLTP at scale
SQL NoSQL
NoSQL solutions using Amazon EC2 and EBS
DB hosted on-premises DB hosted on Amazon EC2
The Forrester Wave™ is copyrighted by Forrester Research, Inc. Forrester and Forrester Wave™ are trademarks of Forrester
Research, Inc. The Forrester Wave™ is a graphical representation of Forrester's call on a market and is plotted using a detailed
spreadsheet with exposed scores, weightings, and comments. Forrester does not endorse any vendor, product, or service depicted in
the Forrester Wave. Information is based on best available resources. Opinions reflect judgment at the time and are subject to change.
The Forrester Wave™: Big Data NoSQL, Q3 2016
Amazon DynamoDB
Run your business, not your database
Fully managed
Fast, consistent performance
Highly scalable
Flexible
Event-driven programming
Fine-grained access control
DynamoDB Benefits
Fully managed service = automated operations
DB hosted on-premises DB hosted on Amazon EC2
Fully managed service = automated operations
DB hosted on premise DynamoDB
Consistently low latency at scale
PREDICTABLE
PERFORMANCE!
WRITES
Replicated continuously to 3 AZs
Persisted to disk (custom SSD)
READS
Strongly or eventually consistent
No latency trade-off
Designed to
support 99.99%
of availability
Built for high
durability
High availability and durability
Customer use cases
Amazon’s Path to DynamoDB
Amazon
DynamoDB
Oracle
Database
MLBAM (MLB Advanced Media) is a full service solutions
provider, operating a powerful content delivery platform.
For the first time, we can
measure things we’ve never
been able to measure
before.
Joe Inzerillo
Executive Vice President and CTO, MLBAM
”
“ • MLBAM can scale to support many games on a
single day.
• Amazon DynamoDB powers queries and supports the
fast data retrieval required.
• MLBAM distributes 25,000 live events annually and
10 million streams daily.
Major League Baseball Fields Big Data,
Excitement with Amazon DynamoDB
Redfin is a full-service real estate company with local
agents and online tools to help people buy & sell homes.
We have billions of records
on DynamoDB being
refreshed daily or hourly or
even by seconds.
Yong Huang
Director, Big Data Analytics, Redfin
”
“ • Redfin provides property and agent details and
ratings through its websites and apps.
• With DynamoDB, latency for “similar” properties
improved from 2 seconds to just 12 milliseconds.
• Redfin stores and processes five billion items in
DynamoDB.
Redfin Is Revolutionizing Home Buying and
Selling with Amazon DynamoDB
Duolingo Scales to Store Over 31 Billion Items
Using DynamoDB
Duolingo is a free language learning service where
users help translate the web and rate translations.
Using AWS, we can handle
traffic spikes that expand up
to seven times the amount of
normal traffic.
Severin Hacker
CTO, Duolingo
”
“
• Duolingo stores data about each user to be able to
generate personalized lessons.
• The MySQL database couldn’t keep up with
Duolingo’s rate of growth
• By using the scalable database service, data store
capacity increased from 100 million to more than four
billion items
• Duolingo has the capacity to scale to support over
8 million active users
Nexon is a leading South Korean video game developer
and a pioneer in the world of interactive entertainment.
By using AWS, we
decreased our initial
investment costs, and only
pay for what we use.
Chunghoon Ryu
Department Manager, Nexon
”
“ • Nexon used Amazon DynamoDB as its
primary game database for a new blockbuster
mobile game, HIT
• HIT became the #1 Mobile Game in Korea
within the first day of launch and has > 2M
registered users
• Nexon’s HIT leverages DynamoDB to deliver
steady latency of less than 10ms to deliver a
fantastic mobile gaming experience for
170,000 concurrent players
Nexon Scales Mobile Gaming with Amazon
DynamoDB
Ad Tech Gaming MobileIoT Web
Scaling high-velocity use cases with DynamoDB
That sounds really good. How
do I get started?
Let’s create a table..
Products
Product_Id
DynamoDB table structure
Table
Items
Attributes
Partition
key
Sort
key
Mandatory
Key-value access pattern
Determines data distribution Optional
Model 1:N relationships
Enables rich query capabilities
All items for key
==, <, >, >=, <=
“begins with”
“between”
“contains”
“in”
sorted results
counts
top/bottom N values
Global secondary index (GSI)
GSIs
A5
(part.)
A4
(sort)
A1
(table key)
A3
(projected)
Table
INCLUDE A3
A4
(part.)
A5
(sort)
A1
(table key)
A2
(projected)
A3
(projected) ALL
A2
(part.)
A1
(table key) KEYS_ONLY
RCU/WCU provisioned
separately for GSIs
Online Indexing
A1
(partition)
A2 A3 A4 A5
Alternate partition (+sort) key
Index is across all table partition keys
Local secondary index (LSI)
Alternate sort key attribute
Index is local to a partition key
A1
(partition)
A3
(sort)
A2
(table key)
A1
(partition)
A2
(sort)
A3 A4 A5
LSIs
A1
(partition)
A4
(sort)
A2
(table key)
A3
(projected)
Table
KEYS_ONLY
INCLUDE A3
A1
(partition)
A5
(sort)
A2
(table key)
A3
(projected)
A4
(projected)
ALL
10 GB max per partition
key, i.e. LSIs limit the #
of sort keys!
Integration capabilities
DynamoDB Triggers
 Implemented as AWS
Lambda functions
 Your code scales
automatically
 Java, Node.js, and Python
DynamoDB Streams
 Stream of table updates
 Asynchronous
 Exactly once
 Strictly ordered
 24-hr lifetime per item
Integration capabilities
• Amazon Elasticsearch Service
integration
• Full-text queries
 Add search to mobile apps
 Monitor IoT sensor status codes
 App telemetry pattern discovery
using regular expressions
• Fine-grained access control by
using AWS Identity and Access
Management (IAM)
• Table-, item-, and attribute-
level access control
Advanced topics in DynamoDB
• Design patterns and best practices
• Data modeling
• Understanding Partitions
• DynamoDB Scaling
Demo
Serverless Web Apps with Amazon
DynamoDB, API Gateway, and AWS Lambda
Simple serverless web application – use case
Elastic event driven applications
Elastic event driven applications
Elastic event driven applications
Elastic event driven applications
Elastic event driven applications
Demo
• Free Tier
 25GB of storage
 25 Reads per second
 25 Writes per second
• Pricing for additional usage in US East (N. Virginia)
 $0.25 per GB per month
 Write throughput: $0.0065 per hour for every 10 units of Write Capacity
 Read throughput: $0.0065 per hour for every 50 units of Read Capacity
DynamoDB Pricing & Free Tier
Resources
Amazon DynamoDB: https://aws.amazon.com/dynamodb/
NoSQL on AWS: https://aws.amazon.com/nosql/document/
Upcoming session: Deep Dive: Amazon DynamoDB
aws.amazon.com/activate
Everything and Anything Startups
Need to Get Started on AWS

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Introduction to Amazon DynamoDB

  • 1. Introduction to Amazon DynamoDB Sean Shriver NoSQL Solutions Architect AWS Solution Architecture 15 March 2017
  • 2. Agenda • Brief history of data processing • Relational (SQL) vs. nonrelational (NoSQL) • NoSQL solutions on AWS • Amazon DynamoDB’s fully managed features • Demo – serverless applications
  • 3. Data volume since 2010 • 90% of stored data generated in last 2 years • 1 terabyte of data in 2010 equals 6.5 petabytes today • Linear correlation between data pressure and technical innovation • No reason these trends will not continue over time
  • 4. Timeline of database technology DataPressure
  • 5. Technology adoption and the hype curve
  • 7. Relational vs. nonrelational databases Traditional SQL NoSQL DB Primary Secondary Scale up DB DB DBDB DB DB Scale out
  • 8. SQL (Relational) Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Products Book Album Movie
  • 9. SQL (Relational) Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Products Book Album Movie Books Title Date Odyssey 1871 Book ID 1 Books Author Homer
  • 10. SQL (Relational) Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Products Book Album Movie Books Title Date Odyssey 1871 Book ID 1 Books Genre Director Drama, Comedy Chaplin Movie ID Title 3 The Kid Movies Author Homer
  • 11. SQL (Relational) Products Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Book Album Movie Books Albums Title Date Odyssey 1871 Book ID 1 Books Albums Title 6 Partitas Album ID Artist 2 Genre Director Drama, Comedy Chaplin Movie ID Title 3 The Kid Movies Bach Author Homer
  • 12. SQL (Relational) Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Books Albums Products Book Album Movie Title Date Odyssey 1871 Book ID 1 Books Albums Title 6 Partitas Album ID Artist 2 Genre Director Drama, Comedy Chaplin Movie ID Title 3 The Kid Movies Tracks Track Partita No. 1 Album ID Track ID 2 1 Bach Author Homer
  • 13. SQL (Relational) vs. NoSQL (Non-relational) Product ID Type Odyssey Homer1 Book ID 2 Album ID 6 Partitas 2 Album ID: Track ID Partita No. 1 Bach Attributes Schema is defined per item Items Partition Key Sort Key 3 Movie ID The Kid Drama, Comedy 1871 Chaplin Primary Key Products Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Title Date Odyssey 1871 Book ID 1 Books Albums Title 6 Partitas Album ID Artist 2 Genre Director Drama, Comedy Chaplin Movie ID Title 3 The Kid Movies Products Book Album Movie Tracks Track Partita No. 1 Album ID Track ID 2 1 Author Homer Bach NoSQL design optimizes for compute instead of storage
  • 14. Why NoSQL? Optimized for storage Optimized for compute Normalized/relational Denormalized/hierarchical Ad hoc queries Instantiated views Scale vertically Scale horizontally Good for OLAP Built for OLTP at scale SQL NoSQL
  • 15. NoSQL solutions using Amazon EC2 and EBS DB hosted on-premises DB hosted on Amazon EC2
  • 16. The Forrester Wave™ is copyrighted by Forrester Research, Inc. Forrester and Forrester Wave™ are trademarks of Forrester Research, Inc. The Forrester Wave™ is a graphical representation of Forrester's call on a market and is plotted using a detailed spreadsheet with exposed scores, weightings, and comments. Forrester does not endorse any vendor, product, or service depicted in the Forrester Wave. Information is based on best available resources. Opinions reflect judgment at the time and are subject to change. The Forrester Wave™: Big Data NoSQL, Q3 2016
  • 17. Amazon DynamoDB Run your business, not your database
  • 18. Fully managed Fast, consistent performance Highly scalable Flexible Event-driven programming Fine-grained access control DynamoDB Benefits
  • 19. Fully managed service = automated operations DB hosted on-premises DB hosted on Amazon EC2
  • 20. Fully managed service = automated operations DB hosted on premise DynamoDB
  • 21. Consistently low latency at scale PREDICTABLE PERFORMANCE!
  • 22. WRITES Replicated continuously to 3 AZs Persisted to disk (custom SSD) READS Strongly or eventually consistent No latency trade-off Designed to support 99.99% of availability Built for high durability High availability and durability
  • 24. Amazon’s Path to DynamoDB Amazon DynamoDB Oracle Database
  • 25. MLBAM (MLB Advanced Media) is a full service solutions provider, operating a powerful content delivery platform. For the first time, we can measure things we’ve never been able to measure before. Joe Inzerillo Executive Vice President and CTO, MLBAM ” “ • MLBAM can scale to support many games on a single day. • Amazon DynamoDB powers queries and supports the fast data retrieval required. • MLBAM distributes 25,000 live events annually and 10 million streams daily. Major League Baseball Fields Big Data, Excitement with Amazon DynamoDB
  • 26. Redfin is a full-service real estate company with local agents and online tools to help people buy & sell homes. We have billions of records on DynamoDB being refreshed daily or hourly or even by seconds. Yong Huang Director, Big Data Analytics, Redfin ” “ • Redfin provides property and agent details and ratings through its websites and apps. • With DynamoDB, latency for “similar” properties improved from 2 seconds to just 12 milliseconds. • Redfin stores and processes five billion items in DynamoDB. Redfin Is Revolutionizing Home Buying and Selling with Amazon DynamoDB
  • 27. Duolingo Scales to Store Over 31 Billion Items Using DynamoDB Duolingo is a free language learning service where users help translate the web and rate translations. Using AWS, we can handle traffic spikes that expand up to seven times the amount of normal traffic. Severin Hacker CTO, Duolingo ” “ • Duolingo stores data about each user to be able to generate personalized lessons. • The MySQL database couldn’t keep up with Duolingo’s rate of growth • By using the scalable database service, data store capacity increased from 100 million to more than four billion items • Duolingo has the capacity to scale to support over 8 million active users
  • 28. Nexon is a leading South Korean video game developer and a pioneer in the world of interactive entertainment. By using AWS, we decreased our initial investment costs, and only pay for what we use. Chunghoon Ryu Department Manager, Nexon ” “ • Nexon used Amazon DynamoDB as its primary game database for a new blockbuster mobile game, HIT • HIT became the #1 Mobile Game in Korea within the first day of launch and has > 2M registered users • Nexon’s HIT leverages DynamoDB to deliver steady latency of less than 10ms to deliver a fantastic mobile gaming experience for 170,000 concurrent players Nexon Scales Mobile Gaming with Amazon DynamoDB
  • 29. Ad Tech Gaming MobileIoT Web Scaling high-velocity use cases with DynamoDB
  • 30. That sounds really good. How do I get started? Let’s create a table..
  • 32.
  • 33. DynamoDB table structure Table Items Attributes Partition key Sort key Mandatory Key-value access pattern Determines data distribution Optional Model 1:N relationships Enables rich query capabilities All items for key ==, <, >, >=, <= “begins with” “between” “contains” “in” sorted results counts top/bottom N values
  • 34. Global secondary index (GSI) GSIs A5 (part.) A4 (sort) A1 (table key) A3 (projected) Table INCLUDE A3 A4 (part.) A5 (sort) A1 (table key) A2 (projected) A3 (projected) ALL A2 (part.) A1 (table key) KEYS_ONLY RCU/WCU provisioned separately for GSIs Online Indexing A1 (partition) A2 A3 A4 A5 Alternate partition (+sort) key Index is across all table partition keys
  • 35. Local secondary index (LSI) Alternate sort key attribute Index is local to a partition key A1 (partition) A3 (sort) A2 (table key) A1 (partition) A2 (sort) A3 A4 A5 LSIs A1 (partition) A4 (sort) A2 (table key) A3 (projected) Table KEYS_ONLY INCLUDE A3 A1 (partition) A5 (sort) A2 (table key) A3 (projected) A4 (projected) ALL 10 GB max per partition key, i.e. LSIs limit the # of sort keys!
  • 36. Integration capabilities DynamoDB Triggers  Implemented as AWS Lambda functions  Your code scales automatically  Java, Node.js, and Python DynamoDB Streams  Stream of table updates  Asynchronous  Exactly once  Strictly ordered  24-hr lifetime per item
  • 37. Integration capabilities • Amazon Elasticsearch Service integration • Full-text queries  Add search to mobile apps  Monitor IoT sensor status codes  App telemetry pattern discovery using regular expressions • Fine-grained access control by using AWS Identity and Access Management (IAM) • Table-, item-, and attribute- level access control
  • 38. Advanced topics in DynamoDB • Design patterns and best practices • Data modeling • Understanding Partitions • DynamoDB Scaling
  • 39. Demo Serverless Web Apps with Amazon DynamoDB, API Gateway, and AWS Lambda
  • 40. Simple serverless web application – use case
  • 41. Elastic event driven applications
  • 42. Elastic event driven applications
  • 43. Elastic event driven applications
  • 44. Elastic event driven applications
  • 45. Elastic event driven applications
  • 46. Demo
  • 47. • Free Tier  25GB of storage  25 Reads per second  25 Writes per second • Pricing for additional usage in US East (N. Virginia)  $0.25 per GB per month  Write throughput: $0.0065 per hour for every 10 units of Write Capacity  Read throughput: $0.0065 per hour for every 50 units of Read Capacity DynamoDB Pricing & Free Tier
  • 48. Resources Amazon DynamoDB: https://aws.amazon.com/dynamodb/ NoSQL on AWS: https://aws.amazon.com/nosql/document/ Upcoming session: Deep Dive: Amazon DynamoDB
  • 49. aws.amazon.com/activate Everything and Anything Startups Need to Get Started on AWS