Database Freedom è un programma realizzato per assistere i clienti che stanno valutando una migrazione dai database tradizionali ai database "cloud native" su AWS. Le applicazioni pensate per il cloud devono essere disponibili a livello globale, operare con latenze che vanno dai microsecondi ai millisecondi, gestire milioni di richieste al secondo, operare senza tempi di inattività, avere un costo ragionevole ed essere gestite in modo efficiente. AWS soddisfa queste esigenze offrendo una gamma di database per ogni tipologia di workload e consentendo ai propri clienti di concentrarsi sulla propria innovazione.

1. © 2019, Amazon Web Services, Inc. or its Affiliates.© 2019, Amazon Web Services, Inc. or its Affiliates.
Database Freedom
Come liberarsi dai database proprietari
15 Maggio 2019

2. © 2019, Amazon Web Services, Inc. or its Affiliates.
What we hear from customers about old-guard databases
AUDIT
Very expensive Proprietary Lock-in Punitive
licensing
You’ve got mail

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Customers are moving to open databases in the cloud.
What is your database strategy ?
‘Lift and shift’ existing
apps to the cloud
Quickly build new
apps in the cloud

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Customers are moving to open databases in the cloud …
‘Lift and shift’ existing
apps to the cloud

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Customers are moving to open databases

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Customers are moving to open databases
+
Commercial-grade performance and reliability ?

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Amazon Aurora
MySQL and PostgreSQL-compatible relational database built for the cloud
Performance and availability of commercial-grade databases at 1/10th the cost
Performance
and scalability
Availability
and durability
Highly secure Fully managed
5x throughput of standard
MySQL and 3x of standard
PostgreSQL; scale-out up to
15 read replicas
Fault-tolerant, self-healing
storage; six copies of data
across three Availability Zones;
continuous backup to Amazon S3
Network isolation,
encryption at
rest/transit
Managed by RDS:
No hardware provisioning,
software patching, setup,
configuration, or backups

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Amazon Aurora
Aurora Global Database Aurora Serverless Aurora Parallel
Query
Designed for globally distributed
applications, allowing a single
database to span multiple AWS
regions
On-demand, auto-scaling
configuration; the database
automatically starts up, shuts
down, and scales capacity up or
down on your application's needs.
Faster analytical queries over your
current data. It can speed up queries
by up to 2 orders of magnitude, while
maintaining high throughput for your
core transactional workload
MySQL and PostgreSQL-compatible relational database built for the cloud
Performance and availability of commercial-grade databases at 1/10th the cost

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Amazon Aurora : fastest growing service in AWS history

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Customer success: Oracle to Aurora
Challenge:
Need better performance at lower cost, to capture a
daily influx of more than 75 billion financial records.
Use case:
Using AWS Database Migration Services to move
databases that ingest and store billions of financial
transaction records from Oracle to Aurora for
greater performance at lower cost.
Saman Michael Far, Senior Vice President & CTO:
“FINRA is in the process of migrating most of our relational databases to
AWS, we have evaluated Amazon Aurora with PostgreSQL compatibility,
and we look forward to increasing our usage, because PostgreSQL is the
best destination for our relational database workloads”

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Customer success stories
“At the UN, we operate multiple websites with global
reach that require mission-critical reliability and
consistent performance.
We were able to achieve superb performance even
with Amazon Aurora’s smallest database engine.
Amazon Aurora’s new user-friendly monitoring
interface made it easy to diagnose and address issues.
Its performance, reliability and monitoring really
shows Amazon Aurora is an enterprise-grade AWS
database”
Mohamad Reza, Information Systems Officer - United Nations

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Amazon Relational Database Service (RDS)
Managed relational database service with a choice of six popular database engines
Easy to administer Available and durable Highly scalable Fast and secure
No need for infrastructure
provisioning, installing, and
maintaining DB software
Automatic Multi-AZ data
replication; automated backup,
snapshots, failover
Scale database compute
and storage with a few
clicks with no app
downtime
SSD storage and guaranteed
provisioned I/O; data
encryption at rest and in
transit

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Hundreds of thousands of customers use Amazon RDS

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Challenge:
Need better performance at lower cost,
to capture fast growing telematics data.
Use case:
Migrated from on-premises Oracle databases to RDS.
Project they will pay about 1/4th of what we were
paying when managing their own private infrastructure.
Customer success: Oracle to RDS

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"Our appeals processing system, VACOLS, includes 20
million records stored in an Oracle 11g database.
The system is more than 20 years old and is in the
process of being modernized. During this time, we
need to ensure that the data is securely replicated
into the cloud for safekeeping.
We're using AWS DMS to replicate the database into
an RDS Oracle database in AWS GovCloud, in a Multi-
AZ deployment.
This setup ensures that VACOLS data is preserved,
secured, and highly available in the cloud, which is a
serious win for VA and for our Veterans, who rely on
us for the safeguarding of their information."
Alan Ning, Site Reliability Engineer, U.S. Digital Service
Customer success: Oracle to RDS

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process more than 2 Exabytes of data

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Customers are creating new apps in the cloud …
Quickly build new
apps in the cloud

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Modern apps create new requirements
Users: 1 million+
Data volume: TB–PB–EB
Locality: Global
Performance: Milliseconds–microseconds
Request rate: Millions
Access: Web, mobile, IoT, devices
Scale: Up-down, Out-in
Economics: Pay for what you use
Developer access: No assembly requiredSocial mediaRide hailing Media streaming Dating

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Break complex apps into smaller pieces and pick the
best tool to solve each problem
This ensures that the apps are well architected and
scale effectively
Developers are now building highly distributed apps
using a multitude of purpose-built databases
Developers are doing what they do best

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Work backward from the problem you are
trying to solve
Choose the right tool for each job

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Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schema-
on-write
Lift and shift, ERP,
CRM, finance
Aurora, RDS
AWS
Service(s)
Common
Use Cases

23. © 2019, Amazon Web Services, Inc. or its Affiliates.
Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schema-
on-write
Lift and shift, ERP,
CRM, finance
Key-value
High
throughput, low-
latency reads
and writes,
endless scale
Real-time bidding,
shopping cart,
social, product
catalog, customer
preferences
AWS
Service(s)
Common
Use Cases
DynamoDBAurora, RDS

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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

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Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schema-
on-write
Lift and shift,
ERP,
CRM,
finance
Key-value
High
throughput, low-
latency reads
and writes,
endless scale
Real-time bidding,
shopping cart,
social, product
catalog, customer
preferences
Document
Store
documents and
quickly access
querying on
any attribute
Content
management,
user profiles,
mobile
AWS
Service(s)
Common
Use Cases
DocumentDBDynamoDBAurora, RDS

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Amazon DocumentDB
Fast, scalable, and fully managed MongoDB-compatible database service
Fast Scalable Fully managed MongoDB
compatible
Millions of requests per second
with millisecond latency; twice
the throughput of MongoDB
Separation of compute and
storage enables both layers
to scale independently;
scale out to 15 read replicas
in minutes
Managed by AWS:
no hardware provisioning;
auto patching, quick setup,
secure, and automatic
backups
Compatible with MongoDB 3.6;
use the same SDKs, tools, and
applications with Amazon
DocumentDB

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Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schema-
on-write
Lift and shift, ERP,
CRM, finance
Key-value
High
throughput, low-
latency reads
and writes,
endless scale
Real-time bidding,
shopping cart,
social, product
catalog, customer
preferences
Document
Store
documents and
quickly access
querying on
any attribute
Content
management,
personalization,
mobile
In-memory
Query by key
with
microsecond
latency
Leaderboards,
real-time analytics,
caching
AWS
Service(s)
Common
Use Cases
ElastiCacheDocumentDBDynamoDBAurora, RDS

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Amazon ElastiCache
Redis and Memcached compatible, in-memory data store and cache
Secure and
reliable
Network isolation,
encryption at rest/transit,
HIPAA, PCI, FedRAMP,
multi AZ, and automatic
failover
Redis & Memcached
compatible
Fully compatible with open
source Redis and Memcached
Easily scalable
Scale writes and reads with
sharding and replicas
Extreme
performance
In-memory data store and
cache for microsecond
response times

29. © 2019, Amazon Web Services, Inc. or its Affiliates.
Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schema-
on-write
Lift and shift, ERP,
CRM, finance
Key-value
High
throughput, low-
latency reads
and writes,
endless scale
Real-time bidding,
shopping cart,
social, product
catalog, customer
preferences
Document
Store
documents and
quickly access
querying on
any attribute
Content
management,
personalization,
mobile
In-memory
Query by key
with
microsecond
latency
Leaderboards,
real-time analytics,
caching
Graph
Quickly and
easily create
and navigate
relationships
between
data
Fraud detection,
social networking,
recommendation
engine
AWS
Service(s)
Common
Use Cases
NeptuneElastiCacheDocumentDBDynamoDBAurora, RDS

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

31. © 2019, Amazon Web Services, Inc. or its Affiliates.
Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schema-
on-write
Lift and shift, ERP,
CRM, finance
Key-value
High
throughput, low-
latency reads
and writes,
endless scale
Real-time bidding,
shopping cart,
social, product
catalog, customer
preferences
Document
Store
documents and
quickly access
querying on
any attribute
Content
management,
personalization,
mobile
In-memory
Query by key
with
microsecond
latency
Leaderboards,
real-time analytics,
caching
Graph
Quickly and
easily create
and navigate
relationships
between
data
Fraud detection,
social networking,
recommendation
engine
Time-series
Collect, store,
and process
data sequenced
by time
IoT applications,
event tracking
AWS
Service(s)
Common
Use Cases
TimestreamNeptuneElastiCacheDocumentDBDynamoDBAurora, RDS

32. © 2019, Amazon Web Services, Inc. or its Affiliates.
Amazon Timestream (sign up for the preview)
Fast, scalable, fully managed time-series database
1,000x faster and 1/10th the
cost of relational databases
Collect data at the rate of
millions of inserts per
second (10M/second)
Trillions of
daily events
Adaptive query processing
engine maintains steady,
predictable performance
Time-series analytics
Built-in functions for
interpolation, smoothing,
and approximation
Serverless
Automated setup,
configuration, server
provisioning, software patching

33. © 2019, Amazon Web Services, Inc. or its Affiliates.
Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schema-
on-write
Lift and shift, ERP,
CRM, finance
Key-value
High
throughput, low-
latency reads
and writes,
endless scale
Real-time bidding,
shopping cart,
social, product
catalog, customer
preferences
Document
Store
documents and
quickly access
querying on
any attribute
Content
management,
personalization,
mobile
In-memory
Query by key
with
microsecond
latency
Leaderboards,
real-time analytics,
caching
Graph
Quickly and
easily create
and navigate
relationships
between
data
Fraud detection,
social networking,
recommendation
engine
Time-series
Collect, store,
and process
data sequenced
by time
IoT applications,
event tracking
Ledger
Complete,
immutable, and
verifiable history
of all changes to
application data
Systems
of record, supply
chain, health care,
registrations,
financial
AWS
Service(s)
Common
Use Cases
QLDBTimestreamNeptuneElastiCacheDocumentDBDynamoDBAurora, RDS

34. © 2019, Amazon Web Services, Inc. or its Affiliates.
Amazon Quantum Ledger Database (QLDB) (Preview)
Fully managed ledger database
Track and verify history of all changes made to your application’s data
Immutable
Maintains a sequenced record of
all changes to your data, which
cannot be deleted or modified;
you have the ability to query and
analyze the full history
Cryptographically
verifiable
Uses cryptography to
generate a secure output
file of your data’s history
Easy to use
Easy to use, letting you
use familiar database
capabilities like SQL APIs
for querying the data
Highly scalable
Executes 2–3X as many
transactions than ledgers
in common blockchain
frameworks

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AWS database services
Purpose-built databases, the right tool for the right job
Database Migration Service
DynamoDB
Key value
Neptune
Graph
ElastiCache
In-memory
Aurora RDS
DocumentDB
Document
QLDB
Ledger
Timestream
Time series
Redshift

36. © 2019, Amazon Web Services, Inc. or its Affiliates.
AWS migration options
AWS DMS
Database migration and
replication managed
service
Benefit
• Easily and securely
migrate and/or
replicate your
databases and data
warehouses to AWS
• Migrate between
different database
engines
• Low cost and global
availability
AWS SCT
Development tooling
to convert schemas
between databases
and data warehouses
Benefit
• Automates schema
conversion including
database structure and
code
• Minimizes manual
effort of performing a
schema re-write
• Allows conversion from
commercial to open
source platforms
Native tooling
Migration options
included with the
engine
Benefit
• Leverage a familiar
environment
• Full support for native
features
Open source
Ora2Pg and others
Benefit
• Tailored solution for a
specific problem
• Multiple tools can offer
a more complete
solution than any one
product
• Free
Commercial
Attunity, Golden Gate
and others
Benefit
• Commercial solutions
are available for a wide
range of migration
sources and targets
including legacy
mainframe systems

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AWS DMS and AWS SCT
AWS SCT converts your commercial database and data
warehouse schemas to open-source engines or AWS-native
services, such as Amazon Aurora and Redshift
AWS DMS easily and securely migrates and/or replicate
your databases and data warehouses to AWS

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Legacy databases to AWS Migration Playbooks
• Topic-by-topic overview of how to migrate databases and
data warehouses to AWS services
• Covers all proprietary features and the different database
objects
• Migration best practices
SCT DMS Playbook
Schema Data Best Practices

39. © 2019, Amazon Web Services, Inc. or its Affiliates.
When to use SCT?
Modernize
&
migrate
Modernize your database tier
Modernize and migrate
Cassandra to Amazon DynamoDB
Amazon Aurora
Amazon Redshift
Modernize and migrate your data
warehouse to Amazon Redshift
Amazon
DynamoDB

40. © 2019, Amazon Web Services, Inc. or its Affiliates.
When to use DMS?
Amazon
Redshift
Amazon
DynamoDB
Amazon S3
Amazon S3
Amazon
Aurora
Amazon
Aurora
Oracle SQL Server Netezza
Greenplum Vertica Teradata
AWS Snowball
Edge
MongoDB Cassandra
Amazon
Elasticsearch
Amazon KinesisAmazon
DocumentDB

41. © 2019, Amazon Web Services, Inc. or its Affiliates.
Customers gaining value from database migrations
Verizon is migrating over 1,000 business-critical applications and database backend systems to AWS, several of
which also include the migration of production databases to Amazon Aurora.
By migrating from Microsoft SQL Server to Amazon Aurora, Ryanair can run one of the largest email
campaigns in Europe with higher performance at a fraction of the cost, sending out 22 million
emails daily to customers.
Intuit migrated from Microsoft SQL Server to Amazon Redshift to reduce data-processing timelines
and get insights to decision makers faster and more frequently.
Equinox Fitness migrated its Teradata on-premises data warehouse to Amazon Redshift. They went
from static reports to a modern data lake that delivers dynamic reports.
Migrated their Market Data system from SQL Server to Aurora MySQL using AWS Database Migration
Service (AWS DMS) to replicate data nightly. Reduces their processing times from 8 hours to 3 hours.
By December 2018, Amazon.com will have migrated 88% of their Oracle DBs (and 97% of critical system
DBs) moved to Amazon Aurora and Amazon DynamoDB. They also migrated their 50 PB Oracle Data
Warehouse to AWS (Amazon S3, Amazon Redshift, and Amazon EMR).
Samsung Electronics migrated their Cassandra clusters to Amazon DynamoDB for their Samsung
Cloud workload with 70% cost savings.

42. © 2019, Amazon Web Services, Inc. or its Affiliates.
Programs
Discover Database Freedom with AWS
Innovation
• Tools: Database Migration Service (DMS) and Schema Conversion Tool (SCT)
• AWS native managed database services
• Optimized and new EC2 and RDS instance types
• ProServe, Partners, Service Teams
• Workload Qualification Framework
• Patterns and Recommendations
Expertise
• AWS Professional Services, partners, product teams
• Migration Playbooks
• Patterns and Recommendations
• Proof-of-concepts
• Workshops
• Incentives & credits
Database Freedom is a unique program designed to assist qualifying customers migrating from traditional
database engines to cloud-native ones on AWS.

43. © 2019, Amazon Web Services, Inc. or its Affiliates.© 2019, Amazon Web Services, Inc. or its Affiliates.
Thank you!