Database Freedom
Come liberarsi dai database proprietari
Fabrizio Celli – AWS Solutions Architect
15 Maggio 2019
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What we hear from customers about old-guard databases
AUDIT
Very expensive
© 2019, Amazon Web Services, Inc. or its Affiliates.
Proprietary
Lock-in
Punitive
licensing
You’ve got mail
Customers are moving to open databases in the cloud.
What is your database strategy ?
‘Lift and shift’ existing
apps to the cloud
© 2019, Amazon Web Services, Inc. or its Affiliates.
Quickly build new
apps in the cloud
Customers are moving to open databases in the cloud
…
‘Lift and shift’ existing
apps to the cloud
© 2019, Amazon Web Services, Inc. or its Affiliates.
Customers are moving to open databases
© 2019, Amazon Web Services, Inc. or its Affiliates.
Customers are moving to open databases
+
Commercial-grade performance and reliability ?
© 2019, Amazon Web Services, Inc. or its Affiliates.
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
5x throughput of standard MySQL
Fault-tolerant, self-healing
and 3x of standard PostgreSQL;
storage; six copies of data
scale-out up to
across three Availability Zones;
15 read replicas
continuous backup to Amazon S3
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Highly secure
Fully managed
Network isolation,
encryption at
rest/transit
Managed by RDS:
No hardware provisioning,
software patching, setup,
configuration, or backups
Amazon Aurora
NEW Features:
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
© 2019, Amazon Web Services, Inc. or its Affiliates.
Aurora: fastest growing service in AWS history
© 2019, Amazon Web Services, Inc. or its Affiliates.
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”
© 2019, Amazon Web Services, Inc. or its Affiliates.
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
© 2019, Amazon Web Services, Inc. or its Affiliates.
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
© 2019, Amazon Web Services, Inc. or its Affiliates.
Customer success: Oracle to RDS
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.
© 2019, Amazon Web Services, Inc. or its Affiliates.
Customer success: Oracle to RDS
"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
© 2019, Amazon Web Services, Inc. or its Affiliates.
© 2019, Amazon Web Services, Inc. or its Affiliates.
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
Ride hailing
Media streaming
© 2019, Amazon Web Services, Inc. or its Affiliates.
Social media
Dating
Developer access: No assembly required
Developers are doing what they do best
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
© 2019, Amazon Web Services, Inc. or its Affiliates.
Work backward from the problem
you are trying to solve
Choose the right tool for each job
© 2019, Amazon Web Services, Inc. or its Affiliates.
Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schemaon-write
Common
Use Cases
AWS
Service(s)
Lift and shift, ERP,
CRM, finance
Aurora, RDS
© 2019, Amazon Web Services, Inc. or its Affiliates.
Common data categories and use cases
Common
Use Cases
AWS
Service(s)
Relational
Key-value
Referential
integrity, ACID
transactions,
schemaon-write
High
throughput, lowlatency reads
and writes,
endless scale
Lift and shift, ERP, Real-time bidding,
shopping cart,
CRM, finance
social, product
catalog, customer
preferences
Aurora, RDS
DynamoDB
© 2019, Amazon Web Services, Inc. or its Affiliates.
Amazon DynamoDB
Fast and flexible key value database service for any scale
Performance at scale
Consistent, single-digit
millisecond response times at
any scale; build applications with
virtually unlimited throughput
© 2019, Amazon Web Services, Inc. or its Affiliates.
Serverless
No server provisioning,
software patching, or
upgrades; scales up or down
automatically; continuously
backs up your data
Comprehensive
security
Global database for
global users and apps
Encrypts all data by
Build global applications with fast
default and fully integrates
access to local data by easily
with AWS Identity and
replicating tables across multiple
Access Management for
AWS Regions
robust security
Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schemaon-write
Common
Use Cases
AWS
Service(s)
Lift and shift,
ERP,
CRM,
finance
Aurora, RDS
Key-value
Document
Store
High
throughput, low- documents and
quickly access
latency reads
querying on any
and writes,
attribute
endless scale
Real-time bidding,
shopping cart,
social, product
catalog, customer
preferences
DynamoDB
© 2019, Amazon Web Services, Inc. or its Affiliates.
Content
management,
user profiles,
mobile
DocumentDB
Amazon DocumentDB
Fast, scalable, and fully managed MongoDB-compatible database service
Fast
Scalable
Millions of requests per second Separation of compute and
with millisecond latency; twice storage enables both layers
the throughput of MongoDB
to scale independently;
scale out to 15 read replicas
in minutes
© 2019, Amazon Web Services, Inc. or its Affiliates.
Fully managed
Managed by AWS:
no hardware provisioning;
auto patching, quick setup,
secure, and automatic
backups
MongoDB
compatible
Compatible with MongoDB 3.6;
use the same SDKs, tools, and
applications with Amazon
DocumentDB
Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schemaon-write
Common
Use Cases
AWS
Service(s)
Key-value
Store
High
throughput, low- documents and
quickly access
latency reads
querying on any
and writes,
attribute
endless scale
Lift and shift, ERP, Real-time bidding,
shopping cart,
CRM, finance
social, product
catalog, customer
preferences
Aurora, RDS
Document
DynamoDB
© 2019, Amazon Web Services, Inc. or its Affiliates.
In-memory
Query by key
with
microsecond
latency
Leaderboards,
Content
management, real-time analytics,
caching
personalization,
mobile
DocumentDB
ElastiCache
Amazon ElastiCache
Redis and Memcached compatible, in-memory data store and cache
Redis & Memcached
compatible
Fully compatible with open
source Redis and Memcached
© 2019, Amazon Web Services, Inc. or its Affiliates.
Extreme
performance
In-memory data store and
cache for microsecond
response times
Secure and
reliable
Easily scalable
Network isolation,
encryption at rest/transit,
HIPAA, PCI, FedRAMP, multi
AZ, and automatic failover
Scale writes and reads with
sharding and replicas
Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schemaon-write
Common
Use Cases
AWS
Service(s)
Key-value
Store
High
throughput, low- documents and
quickly access
latency reads
querying on any
and writes,
attribute
endless scale
Lift and shift, ERP, Real-time bidding,
shopping cart,
CRM, finance
social, product
catalog, customer
preferences
Aurora, RDS
Document
DynamoDB
© 2019, Amazon Web Services, Inc. or its Affiliates.
In-memory
Graph
Query by key
with
microsecond
latency
Quickly and
easily create
and navigate
relationships
between
data
Leaderboards,
Fraud detection,
Content
management, real-time analytics, social networking,
caching
recommendation
personalization,
engine
mobile
DocumentDB
ElastiCache
Neptune
Amazon Neptune
Fully managed graph database
Fast
Query billions of relationships
with millisecond latency
© 2019, Amazon Web Services, Inc. or its Affiliates.
Easy
Open
Build powerful queries
easily with Gremlin and
SPARQL
Supports Apache TinkerPop &
W3C RDF graph models
Reliable
Six replicas of your data across
three AZs with full backup and
restore
Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schemaon-write
Common
Use Cases
AWS
Service(s)
Key-value
Store
High
throughput, low- documents and
quickly access
latency reads
querying on any
and writes,
attribute
endless scale
Lift and shift, ERP, Real-time bidding,
shopping cart,
CRM, finance
social, product
catalog, customer
preferences
Aurora, RDS
Document
DynamoDB
© 2019, Amazon Web Services, Inc. or its Affiliates.
In-memory
Graph
Time-series
Query by key
with
microsecond
latency
Quickly and
easily create
and navigate
relationships
between
data
Collect, store,
and process
data sequenced
by time
Leaderboards,
Fraud detection,
Content
management, real-time analytics, social networking,
caching
recommendation
personalization,
engine
mobile
DocumentDB
ElastiCache
Neptune
IoT applications,
event tracking
Timestream
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)
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Trillions of
daily events
Time-series analytics
Adaptive query processing
engine maintains steady,
predictable performance
Built-in functions for
interpolation, smoothing,
and approximation
Serverless
Automated setup,
configuration, server
provisioning, software patching
Common data categories and use cases
Relational
Referential
integrity, ACID
transactions,
schemaon-write
Common
Use Cases
AWS
Service(s)
Key-value
Store
High
throughput, low- documents and
quickly access
latency reads
querying on any
and writes,
attribute
endless scale
Lift and shift, ERP, Real-time bidding,
shopping cart,
CRM, finance
social, product
catalog, customer
preferences
Aurora, RDS
Document
DynamoDB
© 2019, Amazon Web Services, Inc. or its Affiliates.
In-memory
Graph
Query by key
with
microsecond
latency
Quickly and
easily create
and navigate
relationships
between
data
Leaderboards,
Fraud detection,
Content
management, real-time analytics, social networking,
caching
recommendation
personalization,
engine
mobile
DocumentDB
ElastiCache
Neptune
Time-series
Ledger
Collect, store,
Complete,
and process
immutable, and
data sequenced verifiable history
by time
of all changes to
application data
IoT applications,
event tracking
Timestream
Systems
of record, supply
chain, health care,
registrations,
financial
QLDB
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
© 2019, Amazon Web Services, Inc. or its Affiliates.
Cryptographically
verifiable
Uses cryptography to
generate a secure output
file of your data’s history
Highly scalable
Executes 2–3X as many
transactions than ledgers
in common blockchain
frameworks
Easy to use
Easy to use, letting you
use familiar database
capabilities like SQL APIs
for querying the data
AWS database services
Purpose-built databases, the right tool for the right job
Aurora
RDS
DynamoDB
ElastiCache
Neptune
Key value
In-memory
Graph
DocumentDB
Timestream
QLDB
Document
Time series
Ledger
Redshift
Database Migration Service
© 2019, Amazon Web Services, Inc. or its Affiliates.
AWS DMS and AWS SCT
Our goal: Allow customers the freedom to choose the best data platform for their
needs #DBFreedom
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
© 2019, Amazon Web Services, Inc. or its Affiliates.
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
Schema
Data
Best Practices
SCT
DMS
Playbook
© 2019, Amazon Web Services, Inc. or its Affiliates.
AWS DMS Sources and Targets supported Databases
Sources:
AWS Targets:
Oracle
Microsoft SQL Server
MySQL
MariaDB
PostgreSQL
MongoDB
SAP Adaptive Server Enterprise (ASE)
Db2 for LUW
Azure SQL Database
Amazon S3
Amazon RDS instance databases
Amazon Redshift
Amazon DynamoDB
Amazon S3
Amazon Elasticsearch Service
Amazon Kinesis Data Streams
Amazon DocumentDB
© 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 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).
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.
Samsung Electronics migrated their Cassandra clusters to Amazon DynamoDB for their Samsung
Cloud workload with 70% cost savings.
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.
© 2019, Amazon Web Services, Inc. or its Affiliates.
Discover Database Freedom with AWS
Database Freedom is a unique program designed to assist qualifying customers migrating from traditional
database engines to cloud-native ones on AWS.
Innovation
Expertise
Programs
© 2019, Amazon Web Services, Inc. or its Affiliates.
• Tools: Database Migration Service (DMS) and Schema Conversion Tool (SCT)
• AWS native managed database services
• Optimized and new EC2 and RDS instance types
• AWS
Professional
Services,
• ProServe,
Partners,
Service
Teams partners, product teams
• Migration Playbooks
• Workload Qualification Framework
• Patterns and Recommendations
• Patterns and Recommendations
• Proof-of-concepts
• Workshops
• Incentives & credits
It’s the right moment to be free …
“Blackbird singing in the dead of night
Take these broken wings and learn to fly…
All your life
You were only waiting for this moment to be free”
“ All we have to see
Is that I don't belong to you
And you don't belong to me
Freedom!
Freedom!
Freedom!
You've gotta give for what you take “
© 2019, Amazon Web Services, Inc. or its Affiliates.
“ Man’s red flower
It’s in every living thing
Mind, use your power
Spirit, use your wings
Freedom!
Freedom! “
Q&A
cellifab@
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Thank you!
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