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© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved
Getting Started with Amazon DynamoDB
Padma Malligarjunan
Sr. Technical Account Manager
AWS Enterprise Support
November 02, 2016
Agenda
• Brief history of data processing
• Relational (SQL) vs. nonrelational (NoSQL)
• Fully managed features of DynamoDB
• Customer use cases
• Demo – serverless applications
• Pricing and Free Tier
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 vs. NoSQL schema design
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
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
RDBMS
DynamoDB
Amazon’s Path to DynamoDB
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
Expedia is a leader in the $1 trillion travel industry, with an
extensive portfolio that includes some of the world’s most
trusted travel brands.
With DynamoDB we were up
and running in a less than
day, and there is no need for
a team to maintain.
Kuldeep Chowhan
Principal Engineer, Expedia
”
“ • Expedia’s real-time analytics application collects data
for its “test & learn” experiments on Expedia sites.
• The analytics application processes ~200 million
messages daily.
• Ease of setup, monitoring, and scaling were key
factors in choosing Amazon DynamoDB.
Expedia’s Real-time Analytics Application Uses
Amazon DynamoDB
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
Local secondary index (LSI)
Alternate sort key attribute
Index is local to a partition key
A1
(partition)
A3
(sort)
A2
(item key)
A1
(partition)
A2
(sort)
A3 A4 A5
LSIs A1
(partition)
A4
(sort)
A2
(item key)
A3
(projected)
Table
KEYS_ONLY
INCLUDE A3
A1
(partition)
A5
(sort)
A2
(item key)
A3
(projected)
A4
(projected)
ALL
10 GB maximum per
partition key; LSIs limit the
number of range keys!
Global secondary index (GSI)
Alternate partition and/or sort key
Index is across all partition keys
A1
(partition)
A2 A3 A4 A5
GSIs A5
(partition)
A4
(sort)
A1
(item key)
A3
(projected)
Table
INCLUDE A3
A4
(partition)
A5
(sort)
A1
(item key)
A2
(projected)
A3
(projected) ALL
A2
(partition)
A1
(itemkey) KEYS_ONLY
Online indexing
Read capacity units
(RCUs) and write
capacity units (WCUs)
are provisioned
separately for GSIs
How do GSI updates work?
Table
Primary
table
Primary
table
Primary
table
Primary
table
Global
secondary
index
Client
2. Asynchronous
update (in progress)
If GSIs don’t have enough write capacity, table writes will be throttled!
LSI or GSI?
LSI can be modeled as a GSI
If data size in an item collection > 10 GB, use GSI
If eventual consistency is okay for your scenario, use
GSI!
Advanced topics in DynamoDB
• Data modeling
• Understanding Partitions
• # of partitions depend on table throughput and size
• DynamoDB Scaling
• Design patterns and best practices
To learn more, please attend:
Deep Dive on Amazon DynamoDB
Sean Shriver, AWS NoSQL Solutions Architect
Hands on 90 minute lab (Serverless Web apps)
Sam Elmanak & Scott Kellish
Amazon DynamoDB: https://aws.amazon.com/dynamodb/
Demo
Serverless Web Apps with
Amazon DynamoDB, API
Gateway, and AWS Lambda
Simple serverless web application – use case
Architecture of a simple serverless web
application
Identity & Access
Management
DynamoDBAPI
Gateway
JavaScript
users
S3 Bucket
internet
Lambda
Architecture of a simple serverless web
application
Identity & Access
Management
DynamoDBAPI
Gateway
JavaScript
users
S3 Bucket
internet
Lambda
Architecture of a simple serverless web
application
Identity & Access
Management
DynamoDBAPI
Gateway
JavaScript
users
S3 Bucket
internet
Lambda
Architecture of a simple serverless web
application
Identity & Access
Management
DynamoDBAPI
Gateway
JavaScript
users
S3 Bucket
internet
Lambda
Architecture of a simple serverless web
application
Identity & Access
Management
DynamoDBAPI
Gateway
JavaScript
users
S3 Bucket
internet
Lambda
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
THANK YOU!
Don’t forget…
• SURVEY: emailed to you within 12 hours. We value your feedback!
• SLIDES: links will display on screen when you complete the survey
• MORE QUESTIONS? Visit the Ask an Architect bar on the 1st Floor
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved
aws.amazon.com/activate
Everything and Anything Startups
Need to Get Started on AWS

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Getting started with Amazon Dynamo BD

  • 1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved Getting Started with Amazon DynamoDB Padma Malligarjunan Sr. Technical Account Manager AWS Enterprise Support November 02, 2016
  • 2. Agenda • Brief history of data processing • Relational (SQL) vs. nonrelational (NoSQL) • Fully managed features of DynamoDB • Customer use cases • Demo – serverless applications • Pricing and Free Tier
  • 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 vs. NoSQL schema design NoSQL design optimizes for compute instead of storage
  • 9. 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
  • 10. Amazon DynamoDB Run your business, not your database
  • 11. Fully managed Fast, consistent performance Highly scalable Flexible Event-driven programming Fine-grained access control DynamoDB Benefits
  • 12. Fully managed service = automated operations DB hosted on-premises DB hosted on Amazon EC2
  • 13. Fully managed service = automated operations DB hosted on premise DynamoDB
  • 14. Consistently low latency at scale PREDICTABLE PERFORMANCE!
  • 15. 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
  • 18. 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
  • 19. 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
  • 20. Expedia is a leader in the $1 trillion travel industry, with an extensive portfolio that includes some of the world’s most trusted travel brands. With DynamoDB we were up and running in a less than day, and there is no need for a team to maintain. Kuldeep Chowhan Principal Engineer, Expedia ” “ • Expedia’s real-time analytics application collects data for its “test & learn” experiments on Expedia sites. • The analytics application processes ~200 million messages daily. • Ease of setup, monitoring, and scaling were key factors in choosing Amazon DynamoDB. Expedia’s Real-time Analytics Application Uses Amazon DynamoDB
  • 21. 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
  • 22. Ad Tech Gaming MobileIoT Web Scaling high-velocity use cases with DynamoDB
  • 23. That sounds really good. How do I get started? Let’s create a table..
  • 25.
  • 26. 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
  • 27. Local secondary index (LSI) Alternate sort key attribute Index is local to a partition key A1 (partition) A3 (sort) A2 (item key) A1 (partition) A2 (sort) A3 A4 A5 LSIs A1 (partition) A4 (sort) A2 (item key) A3 (projected) Table KEYS_ONLY INCLUDE A3 A1 (partition) A5 (sort) A2 (item key) A3 (projected) A4 (projected) ALL 10 GB maximum per partition key; LSIs limit the number of range keys!
  • 28. Global secondary index (GSI) Alternate partition and/or sort key Index is across all partition keys A1 (partition) A2 A3 A4 A5 GSIs A5 (partition) A4 (sort) A1 (item key) A3 (projected) Table INCLUDE A3 A4 (partition) A5 (sort) A1 (item key) A2 (projected) A3 (projected) ALL A2 (partition) A1 (itemkey) KEYS_ONLY Online indexing Read capacity units (RCUs) and write capacity units (WCUs) are provisioned separately for GSIs
  • 29. How do GSI updates work? Table Primary table Primary table Primary table Primary table Global secondary index Client 2. Asynchronous update (in progress) If GSIs don’t have enough write capacity, table writes will be throttled!
  • 30. LSI or GSI? LSI can be modeled as a GSI If data size in an item collection > 10 GB, use GSI If eventual consistency is okay for your scenario, use GSI!
  • 31. Advanced topics in DynamoDB • Data modeling • Understanding Partitions • # of partitions depend on table throughput and size • DynamoDB Scaling • Design patterns and best practices
  • 32. To learn more, please attend: Deep Dive on Amazon DynamoDB Sean Shriver, AWS NoSQL Solutions Architect Hands on 90 minute lab (Serverless Web apps) Sam Elmanak & Scott Kellish Amazon DynamoDB: https://aws.amazon.com/dynamodb/
  • 33. Demo Serverless Web Apps with Amazon DynamoDB, API Gateway, and AWS Lambda
  • 34. Simple serverless web application – use case
  • 35. Architecture of a simple serverless web application Identity & Access Management DynamoDBAPI Gateway JavaScript users S3 Bucket internet Lambda
  • 36. Architecture of a simple serverless web application Identity & Access Management DynamoDBAPI Gateway JavaScript users S3 Bucket internet Lambda
  • 37. Architecture of a simple serverless web application Identity & Access Management DynamoDBAPI Gateway JavaScript users S3 Bucket internet Lambda
  • 38. Architecture of a simple serverless web application Identity & Access Management DynamoDBAPI Gateway JavaScript users S3 Bucket internet Lambda
  • 39. Architecture of a simple serverless web application Identity & Access Management DynamoDBAPI Gateway JavaScript users S3 Bucket internet Lambda
  • 40. Demo
  • 41.
  • 42. • 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
  • 43. THANK YOU! Don’t forget… • SURVEY: emailed to you within 12 hours. We value your feedback! • SLIDES: links will display on screen when you complete the survey • MORE QUESTIONS? Visit the Ask an Architect bar on the 1st Floor
  • 44. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved aws.amazon.com/activate Everything and Anything Startups Need to Get Started on AWS