NoSQL is a term used to describe high-performance, non-relational databases. NoSQL databases use a variety of data models, including document, graph, and key-value. NoSQL databases are recognized for ease of development, scalable performance, high availability, and resilience. With AWS, you can use fully-managed NoSQL database services such as Amazon DynamoDB for all applications that need consistent, single-digit millisecond latency at any scale; Amazon Neptune, a graph database built for the cloud; and Amazon ElastiCache, an in-memory data store service where you can choose Redis or Memcached to power your real-time applications.

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Tobias Börjeson
Solutions Architect, AWS
Peter Düsterdich
Head of Game Reliability Engineering Team, MovieStarPlanet
Managed NoSQL databases

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Characteristics of Internet Scale Applications
Key-valueRelational Document Graph
;
Users >1M
Data volume TB-PB-EB
Locality Global
Performance Milliseconds-Microseconds
Request rate Millions
Access Mobile, IoT, Devices
Scale Up-Out-In
Economics Pay as you go
Developer access Instant API access

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purpose
noun | pur·pose | ˈpər-pəs
The reason for which something is done or created
or for which something exists

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Driving Adoption of Non-relational Databases
Addressing need for massive scale, low latency, and schema flexibility
Referential integrity with
strong consistency,
transactions, and hardened
scale
GraphKey value Document
;
Relational
Low latency key-based
queries with high
throughput and fast
ingestion of data
Indexing and storing
documents with support
for query on any
property
Creating and
navigating relations
between data quickly
and easily
Complex query support
via SQL
Simple query methods
with filters
Simple query with filters,
projections, and
aggregates
Easily express queries in
terms of relations
Non-relational

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Non-relational
Amazon DynamoDB Amazon ElastiCache
Key value | Document
Non-relational
AWS Database Migration Service
Amazon Neptune
Graph
AWS Non-relational Databases
Purpose built for specific application use cases

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Amazon DynamoDB
Fast and flexible NoSQL database service for any scale
Fast, consistent
performance
Highly scalable Fully managed Business critical
reliability
Consistent single-digit
millisecond latency; DAX in-
memory performance reduces
response times to microseconds
Automatic scaling to
hundreds of terabytes of
data that serve millions
of requests per second
Automatic provisioning,
infrastructure
management, scaling,
and configuration with
zero downtime
Data is replicated across
fault-tolerant Availability
Zones, with fine-grained
access control

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Amazon DynamoDB Schema
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

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Server 1
T1.p1
Table1 Table2 Table3
Server N
T1.p2
Behind the scenes…
1K WCU or 3K RCU
Up to 10 GB

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VPC
Endpoints
April 2017
Auto
Scaling
June 2017
DynamoDB
Accelerator (DAX)
April 2017
Time to
Live (TTL)
February 2017
Global Tables
N E W !
Backup and
Restore
N E W !
Amazon DynamoDB
Delivering on customer needs
Encryption at rest
N E W !
February 2018November 2017November 2017

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ID Name Size Expiry
1234 A 100 1456702305
2222 B 240 1456702400
3423 C 150 1459207905
• Automatically delete items from a table based on
expiration time stamp
• User-defined TTL attribute in epoch time format
• TTL activity recorded in DynamoDB Streams
TTL Attribute
Features
Key benefits
• Reduce costs by deleting items no longer needed
• Optimize application performance by controlling
table size growth
• Trigger custom workflows with Streams and
Lambda
Scaling Storage: Time-to-live (TTL)

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Amazon VPC Endpoints
• Access DynamoDB via secure Amazon Virtual
Public Cloud (Amazon VPC) endpoint
• Control access to tables via each VPC endpoint
with unique IAM roles and permissions
Features
Key benefits
• Turn off access from public internet gateways
enhancing privacy and security
• Fast, secure data transfer between Amazon VPC
and DynamoDB

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DynamoDB Accelerator (DAX)
In-memory performance and throughput. More than an order of magnitude faster!
Milliseconds to
microseconds

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Scaling Throughput: Auto Scaling
$$$ Savings

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DynamoDB Global Tables
First fully managed, multi-master, multi-region database
Build high performance, globally distributed
applications
Low latency reads & writes to locally available
tables
Disaster proof with multi-region redundancy
Easy to set up, and no application rewrites
required
Globally dispersed users
Replica (N. America)
Replica (Europe)
Replica (Asia)
Global app
Global Table
NEW!

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Amazon DynamoDB – Backup and Restore
First NoSQL database to automate on demand and continuous backups
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
NEW!

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Amazon DynamoDB
Encryption at rest
Server-side
encryption
Support
compliance
certifications
No application
code rewrites
NEW!

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Internet scale applications need low latency and high throughput
In-memory data stores and caches:
• Deliver sub-millisecond performance
• Deliver high throughput to support millions of users
• Significantly reduce cost-at-scale
Gaming
leaderboards
Social
media
Ride
hailing
Session
stores
Media
streaming
Dating
Why Use In-Memory Data Stores and Caches

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Amazon ElastiCache
Fully managed, Redis or Memcached compatible, in-memory data store and cache
Extreme performance Secure & hardened Easily scalable Highly available & reliable
In-memory data store and
cache for sub-millisecond
response times
VPC for cluster isolation,
encryption at rest and
transit, and HIPAA
compliance
Read scaling with
replicas, write and
memory scaling with
sharding, undisruptive
scaling
Multi-AZ with automatic
failover

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Amazon ElastiCache
Online cluster resizing Encryption Compliance R4 Instances
Scale-out or scale-in
Redis clusters
without downtime
Secure internode
communications &
backups
Scale to 6.1 TiB of in-
memory data for Redis
and 8.14 TiB for
Memcached
HIPAA eligibility for
ElastiCache for Redis
NEW in the last 12 months!

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0–5461
Shard 1 Shard 2 Shard 3
5462–10922 10923–16383
aws elasticache modify-replication-group-shard-configuration --replication-group-id
rep-group-id
--apply-immediately --node-group-count 5
Simple API
Scale in || Out
Online Cluster Resizing – Zero Downtime

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0–5461
Reads & writes
Shard 1 Shard 2 Shard 3
Added Added
Shard 4 Shard 5
5462–10922 10923–163830–2909,
5095–5461
5462–5783,
6876–9830
10923–14199
2910–5094,
9831–10922
No application interruption
Uniform slot distribution across shards
5784–6875,
14200–16383
Online Cluster Resizing – Scale Out

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0–5461
Reads & writes
Shard 1 Shard 2 Shard 3
Removed Removed
Shard 4 Shard 5
5462–10922 10923–16383
Uniform slot distribution across shards
No application interruption
Online Cluster Resizing – Scale In

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Encryption and Compliance
Encryption
• In-transit: Encrypt all communications between clients and
Redis server as well as between nodes
• At-rest: Encrypt backups on disk and in Amazon S3
• Fully managed: Set up via API or console, automatic
issuance, and renewal
Compliance
• HIPAA eligibility for ElastiCache for Redis
• Included in AWS Business Associate Addendum
• Redis 3.2.6

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Other Launches
R4 instances
• Scale to 64 vCPUs, 488 GiB DDR4 memory, and 20-GiB network
• With Redis cluster, customers can scale to 6.1 TiB of memory
Flexible reconfiguration
• Launched February 2017
• Flexible reconfiguration based on backup and restore
• Allows going from noncluster mode to cluster mode
• Change replication factor
• Change number of shards
Test failover

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Session
management
Database caching APIs
(HTTP responses)
IoT
Real-time data
analytics
(filtering/aggregation)
Pub/Sub
Social media
(Sentiment analysis)
Standalone
database
(metadata store)
Gaming
leaderboards
Usage Patterns

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Caching

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Real-time Analytics

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Gaming Leaderboards

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Highly Connected Data Best Represented in a Graph
Social news feed Restaurant recommendations Retail fraud detection
Is friend of Likes
Likes
Serves
Serves
Located in
Location:
New York
Name:
Sushi
Name:
Sushi
Cuisine:
Sushi
Located in
Is friend of
Friends
Use Like Like Connect
Play Check In Read
Country City Address
Credit Card
Email Address
Date
Product
IP Order
Person
Phone

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Too expensive
Difficult to maintain
high availability
Difficult to scale
Limited support for
open standards
$
Existing Graph DatabasesRelational Databases
Inefficient graph
processing
Unnatural for
querying graph
Rigid schema inflexible
for changing graphs
Challenges building apps with highly connected data

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Amazon Neptune
Fully managed graph database
Fast & scalable ReliableOpen
Query billions of
relationships with
millisecond latency
Six replicas of your data
across three AZs with
full backup and restore
Build powerful
queries easily with
Gremlin and SPARQL
Supports Apache
TinkerPop & W3C
RDF graph models
Easy
Gremlin
SPARQL

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Customers of AWS Non-relational Databases

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AWS databases and analytics
Broad and deep portfolio, purpose-built for builders
DW | Big Data Processing | Interactive
Business Intelligence & Machine Learning
Data Movement
Database Migration Service | Snowball | Snowmobile | Kinesis Data Firehose | Kinesis Data Streams
Amazon QuickSight
Relational Databases
RDS
Aurora
Data Lake
Amazon S3/Amazon Glacier AWS Glue
(ETL & Data Catalog)
SageMaker
Non-Relational Databases Analytics
DynamoDB
ElastiCache
(Redis, Memcached)
Neptune
(Graph)
Amazon
Redshift
EMR Athena
Kinesis
Data
Analytics
Elasticsearch
Service
Real-time
Amazon Comprehend

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