NoSQL databases are a great fit for many modern applications such as mobile, web, and gaming that require flexible, scalable, high-performance, and highly functional databases to provide great user experiences but they can be hard to manage and require high proficiency and attention.In this session we will present Amazon DynamoDB, a fully managed, multi-region, multi-master database that provides consistent single-digit millisecond latency in any scale.

2. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
No Hassle, NoSQL
DynamoDB, DocumentDB
Leonid Koren
Solutions Architect
AWS
D A T 3 0 4
Ziv Shenhav
Technical Account Manager
AWS
Inbar Yogev
Data Engineering Lead
Riskified
Drorit Baron
Software Developer
Riskified

3. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Agenda
• NoSQL Databases
• DynamoDB
• Managing Table Capacity (under the hood)
• Features for Developers
• Customer Story
• DocumentDB

4. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Optimized for storage Optimized for compute
Normalized/relational Denormalized/hierarchical
Ad hoc queries Instantiated views
Scale vertically Scale horizontally
Good for OLAP, Limited Scale OLTP Built for OLTP at scale
SQL NoSQL
Why NoSQL?

5. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Operating Self-Managed NoSQL Is Challenging
It’s too much work
It costs too much

6. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Amazon DynamoDB
Fast and flexible key value database service for any scale
Comprehensive
security
Encrypts all data by
default and fully integrates
with AWS Identity and
Access Management for
robust security
Performance at scale
Consistent, single-digit
millisecond response times at
any scale; build applications with
virtually unlimited throughput
Global database for
global users and apps
Build global applications with
fast access to local data by easily
replicating tables across multiple
AWS Regions
Serverless
No server provisioning,
software patching, or
upgrades; scales up or down
automatically; continuously
backs up your data

7. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Table, Item, Attribute, Index
Table
Items
Attributes
Partition
Key
Sort
Key
Customer ID
(Partition Key)
Order Date
(Sort Key)
Store Order Sum Country
Local Secondary Index
Example Table
Customer ID
(Partition Key)
Order Sum
(Sort Key)
Order Date
Country
(Partition Key)
Order Sum Store Order DateGlobal Secondary Index

8. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
00 55 A954 FFAA00 FF
Partition Keys
Partition Key uniquely identifies an item
Partition Key is used for building an unordered hash index
Allows table to be partitioned for scale
Id = 1
Name = Jim
Hash (1) = 7B
Id = 2
Name = Andy
Dept = Eng
Hash (2) = 48
Id = 3
Name = Kim
Dept = Ops
Hash (3) = CD
Key Space

9. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Partitions are replicated across three AZs
Id = 2
Name = Andy
Dept = Engg
Id = 3
Name = Kim
Dept = Ops
Id = 1
Name = Jim
Id = 2
Name = Andy
Dept = Engg
Id = 3
Name = Kim
Dept = Ops
Id = 1
Name = Jim
Id = 2
Name = Andy
Dept = Engg
Id = 3
Name = Kim
Dept = Ops
Id = 1
Name = Jim
Replica 1
Replica 2
Replica 3

10. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

11. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Provisioning Table Capacity

12. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Provisioning Table Capacity
1 RCU = Items up to 4KB
1 WCU = Items up to 1KB

13. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Provisioning Trade-off

14. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Provisioning Example

15. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
0x12A8 236294 { name:“Sara”, city:”Tampa”, …}
0x3391 445104 { name:“James”, city:”Miami”, …}
0x6134 333363 { name:“Betty”, city:”Madison”, …}
0x9531 145783 { name:“Bob”, city:”London”, …}
0xB082 643145 { name:“Val”, city:”Seattle”, …}
0xEA8A 723342 { name:“Jeff”, city:”Toledo”, …}
0xF355 523422 { name:“Alex”, city:”London”, …}
Provisioning

16. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Token Bucket Algorithm

17. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Burst Capacity

18. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Unbalanced Load
0x12A8 236294 { name:“Sara”, city:”Tampa”, …}
0x3391 445104 { name:“James”, city:”Miami”, …}
0x6134 333363 { name:“Betty”, city:”Madison”, …}
0x9531 145783 { name:“Bob”, city:”London”, …}
0xB082 643145 { name:“Val”, city:”Seattle”, …}
0xEA8A 723342 { name:“Jeff”, city:”Toledo”, …}
0xF355 523422 { name:“Alex”, city:”London”, …}

19. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Unbalanced Load
0x12A8 236294 { name:“Sara”, city:”Tampa”, …}
0x3391 445104 { name:“James”, city:”Miami”, …}
0x6134 333363 { name:“Betty”, city:”Madison”, …}
0x9531 145783 { name:“Bob”, city:”London”, …}
0xB082 643145 { name:“Val”, city:”Seattle”, …}
0xEA8A 723342 { name:“Jeff”, city:”Toledo”, …}
0xF355 523422 { name:“Alex”, city:”London”, …}
50 throttles
per second

20. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Adaptive Capacity

21. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Adaptive Capacity

22. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Adaptive Capacity Active
0x12A8 236294 { name:“Sara”, city:”Tampa”, …}
0x3391 445104 { name:“James”, city:”Miami”, …}
0x6134 333363 { name:“Betty”, city:”Madison”, …}
0x9531 145783 { name:“Bob”, city:”London”, …}
0xB082 643145 { name:“Val”, city:”Seattle”, …}
0xEA8A 723342 { name:“Jeff”, city:”Toledo”, …}
0xF355 523422 { name:“Alex”, city:”London”, …}

23. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Total Demand Change
0x12A8 236294 { name:“Sara”, city:”Tampa”, …}
0x3391 445104 { name:“James”, city:”Miami”, …}
0x6134 333363 { name:“Betty”, city:”Madison”, …}
0x9531 145783 { name:“Bob”, city:”London”, …}
0xB082 643145 { name:“Val”, city:”Seattle”, …}
0xEA8A 723342 { name:“Jeff”, city:”Toledo”, …}
0xF355 523422 { name:“Alex”, city:”London”, …}
à
à
à

24. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Auto Scaling

25. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Actual Auto-scaled Table

26. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Auto Scaling – Creating A New Table

27. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Provisioning Recap

28. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
DynamoDB On-Demand
Features
• No capacity planning, provisioning, or
reservations - simply make API calls
• Pay only for the reads and writes you perform
Key benefits
• Eliminates tradeoffs of over- or under-
provisioning
• Instantly accommodates your workload as traffic
ramps up or down

29. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
DynamoDB On-Demand

30. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
DynamoDB On-Demand

31. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
DynamoDB: Capacity managed for you
Govern max consumption

32. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

33. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
DynamoDB transactions
Simplify your code by executing multiple, all-or-nothing
actions within and across tables with a single API call
Single
API
Call

34. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Global Tables
Build high-performance, globally
distributed applications.
Low latency reads and writes
to locally available tables.
Multi-region redundancy
and resiliency.
Easy to set up, and no application
re-writes required.

35. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
DynamoDB Streams
• DynamoDB Streams captures a time-ordered sequence of item-
level modifications (stored up to 24 hours) in a DynamoDB table
• Process multiple modifications at a time with Lambda
Amazon
DynamoDB
DynamoDB
Stream
AWS Lambda
function

36. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Time-To-Live (TTL)
TTL job
CustomerActiveOrder
OrderId: 1
CustomerId: 1
Removes data that is no longer relevant
MyTTL: 1492641900

37. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Point in time restore
for short-term
retention and data
corruption protection
Backup hundreds of
TB instantly with NO
performance impact
On-demand
backups for long-
term data archival
and compliance
Backup and Restore

38. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Riskified DynamoDB
talk for AWS summit
Inbar Yogev
Data Engineering Lead
Riskified
Drorit Baron
Software Developer
Riskified

39. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Meet Riskified
We’re an AI platform helping merchants optimize the online shopping journey
Login Checkout Post CheckoutAuthorization Fraud Review
Over 300
employees
200% CAGR
(2014-2018)
$64 million
in funding

40. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Riskified’s solution is effective across all online industries
Marketplaces High-End Fashion Electronics
GiftcardsTravelHome
Sneakers Big Box Retail Automobile Jewelry/ Precious Metals

41. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
ClickStream Analysis
Behavioral analysis
Device
fingerprinting
Proxy
detection
Research
Real-time
analysis
120K events
/ second
200 reads
/ second

42. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Old Architecture
Replica set Sharded cluster
15 Shards
(30 nodes total)
MongoDB MongoDB
Research
Real-time
analysis

43. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
New Architecture
Kinesis
Data Streams
DynamoDB
Redshift Research
Real-time
analysis

44. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Data Model
The Mongo Era The DynamoDB Era
Nested documents (JSON)
Partition keys
Sort keys
Indexes Lookup tables
Manually purge TTL

45. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
OPS
The Mongo Era The DynamoDB Era
Complex installation Zero installation
Limited metrics Usable metrics
Complex DR Easy DR

46. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Transaction Performance
99%
95%
AVG

47. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Scaling
The Mongo Era The DynamoDB Era
Weeks Minutes

48. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Costs Prediction
30K $
10K $

49. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Join Our Team
Team members across our offices
in Tel Aviv and NYC, and growing!
300
Talented team members in R&D.
45

50. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Join Our Team
Come be part of the eCommerce revolution and join us
for the ride!
To learn more and apply: www.riskified.com/careers
Our stack includes RDS, Redshift,
Elasticsearch, DynamoDB, Redis,
Amazon Kinesis, Kafka, and Spark.
We're looking for Big Data
Engineers, Backend, and Fullstack
Developers to join us.

51. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Thank you for
your time!
For additional information, visit:
www.riskified.com

52. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

53. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
AWS databases services
Purpose-built for all your app needs
NeptuneRDS
Aurora CommercialCommunity
Timestream QLDBElastiCache
Relational Key-value Document In-memory Graph Time series Ledger
DynamoDB
DocumentDB
NEW!
Redis Memcached

54. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Document databases
• Data is stored in JSON-like
documents
• Documents map naturally to
how humans model data
• Flexible schema and indexing
• Expressive query language
built for documents (ad hoc
queries and aggregations)
JSON documents are first-class objects
of the database
{
id: 1,
name: "sue",
age: 26,
email: "sue@example.com",
promotions: ["new user", "5%", "dog lover"],
memberDate: 2018-2-22,
shoppingCart: [
{product:"abc", quantity:2, cost:19.99},
{product:"edf", quantity:3, cost: 2.99}
]
}

55. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Amazon DocumentDB
Fast, scalable, highly available MongoDB-compatible database
Highly Available
Automatic Multi-AZ data
replication; automated
backup, snapshots,
failover;
Performance at scale
2X the throughput of currently
available MongoDB managed
services; scale read capacity to
millions of requests per second
by adding up to 15 low latency
read replicas across three AZs in
minutes, regardless of data size
MongoDB-compatible
Implements the Apache 2.0 open
source MongoDB 3.6 API by
emulating the responses that a
MongoDB client expects from a
MongoDB server
Durable
Fault-tolerant, self-healing
storage; six copies of data
across three Availability Zones;
continuous backup to Amazon
S3

56. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
reads
AWS Region
Availability Zone 1 Availability Zone 2 Availability Zone 3
Instance
(primary)
Cluster volume
Instance
(replica)
Instance
(replica)
Data copies Data copies Data copies
writes
writes
writes
reads
reads
Amazon DocumentDB Architecture
Separate compute and storage

57. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Distributed Storage Volume Distributed Storage Volume Distributed Storage Volume
Scenario 1: Dev/test with a single
instance
Scenario 2: Read scaling in minutes Scenario 3: Scale-up and scale-out for
analytics
Flexible
Durability and replication are handled by the distributed storage volume

58. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Fully-managed
Fast, reliable, and fully-managed MongoDB-compatible database service
Automatic patching Quick start Monitoring Integrated
Up-to-date with the latest
patches
Provision production-
ready clusters in minutes
Over 20 key operational
metrics for your clusters
at no extra charge
Deeply integrated with AWS
services such as
CloudFormation, CloudTrail,
CloudWatch, DMS, IAM, VPC,
and more.

59. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Backup
Automatic backups 35 days of
PITR
Archive snapshots
Automatic, incremental, and
continuous backups
Backups do not affect
database performance
Point-in-time recovery
(PITR) for up to 35 days
Keep snapshots for as long as
you need
No performance
impact

60. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Migrate on-premises MongoDB
databases to DocumentDB
Migrate EC2 MongoDB
databases to DocumentDB
Data replication for near-zero
downtime migration
Migrate from replica sets and
sharded clusters
Migration
Migrate to DocumentDB with the Amazon Database Migration Service (DMS)
Free for 6 months if you are
moving to DocumentDB

61. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Which database to use?
• Key-value
• Hyper Scale
• Consistent low latency at any
scale
• Multi-master with global
replication
• Item size up to 400KB
DynamoDB DocumentDB
• Documents
• Efficiently query nested structures
• Rich suite of query operators
• Aggregations
• Document size up to 16MB
• Database size up to 64TB
• Simple migration for existing
MongoDB users

62. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

63. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Thank you!
© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Leonid Koren
Solutions Architect - AWS
http://bit.ly/2SGYFNY
Ziv Shenhav
Technical Account Manager - AWS