If you are still running proprietary, highly expensive databases and open to learn about alternatives - this session is aimed for you. In this session we will discuss how AWS helps customers modernizing their databases to get aligned with the modern applications requirements, while achieving operational excellence and cost efficiency.

1. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
SSID: Guest
Password: Cube@11999
Database Freedom
Ronen Amrani
Solutions Architect

2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Traditional Application Requirements
Users: 10–100k
Data volume: GB–TB
Locality: HQ
Performance: Seconds
Request Rate: Tens of thousands
Access: Internal servers, PCs
Scale: Up
Economics: Pay up front
Developer Access: Days/weeks/months
HR Payroll …
CRM ERP

3. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Modern Application Requirements
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
Relational Key-value Document
In-memory Graph

4. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Are you operating with old world databases?
AUDIT
Very expensive Proprietary Lock-in Punitive
licensing
You’ve got mail

5. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Programs
Discover Database Freedom with AWS
Innovation
• Database Migration Service and Schema Conversion Tool
• Aurora MySQL and Aurora PostgreSQL, RDS for Open Source databases
• DynamoDB with DAX, EMR, Redshift and Spectrum, and other services
• New EC2 instance types
• ProServe, Partners, Service Teams
• Workload Qualification Framework
• Patterns and Recommendations
Expertise
• Professional Services, Partners, Service Teams
• Workload Qualification Framework
• Patterns and Recommendations
• Workshops
• Proofs-of-Concepts
• Incentives (e.g. MAP)

6. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Database Services
Amazon Aurora
High-Performance Managed
Relational Database
Benefit
• MySQL and PostgreSQL
compatible relational
database with several times
better performance
• Security, availability, and
reliability of commercial
databases at 1/10th the cost
Amazon RDS
Managed Relational
Database Service for
MySQL, PostgreSQL,
Oracle, SQL Server, and
MariaDB
Benefit
• Set up, operate, and scale a
relational database in the
cloud with just a few clicks
Amazon DynamoDB
Managed NoSQL
Database
Benefit
• Fast and flexible NoSQL
database service for any
scale
• Pay only for the throughput
and storage you need
Amazon Redshift
Fast, simple, cost-
effective data
warehousing
Benefit
• Simple and cost effective to
analyze data using standard
SQL and your existing
Business Intelligence (BI)
tools
Amazon EMR
Managed Hadoop
framework
Benefit
• Easily run and scale Apache
Hadoop, Spark, HBase,
Preso, Hive, and other Big
Data frameworks

7. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Market Leadership
The Forrester Wave™ is copyrighted by Forrester Research, Inc. Forrester and Forrester Wave™ are trademarks of Forrester Research, Inc. The Forrester Wave™ is a graphical representation of
Forrester's call on a market and is plotted using a detailed spreadsheet with exposed scores, weightings, and comments. Forrester does not endorse any vendor, product, or service depicted in the
Forrester Wave. Information is based on best available resources. Opinions reflect judgment at the time and are subject to change.
Forrester Research positions Amazon Web
Services as a Leader in The Forrester WaveTM:
Database-as-a-Service.
“AWS not only has the largest adoption of
DBaaS, it also offers the widest range of
offerings to support analytical, operational, and
transactional workloads.”
“AWS’s key strengths lay in its dynamic scale,
automated administration, flexibility of database
offerings, strong security, and high-availability
capabilities, which make it a preferred choice for
customers”

8. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
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

9. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Customer Experiences
AstraZeneca reduced processing
time from 26 hours to 40 minutes by
migration from Oracle stack to Aurora
MySQL stack
Blackboard migrated their Learning
Management System to RDS PostgreSQL
to better compete against emerging
competition. With licensing reduction
failover became affordable for their clients
and is used in all deployments.
Verizon is targeting a mass migration
off of Oracle to PostgreSQL. One
project projects potential savings of
$1.75M
Trimble Leveraged SCT to determine
target engine. Reduced infrastructure
costs to less than one-fourth of their
privately hosted infrastructure
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.
Migrated their Market Data system from
SQL Server to Aurora MySQL using AWS
Database Migration Service(DMS) to
replicate data nightly. Reduces their
processing times from 8 hours to 3.

10. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Database Freedom Program

11. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Database Freedom Program options
database
freedom program
Large Scale Re-PlatformingProject Based Validation
Objective: Proof of Concept (POC) Projects
• Address technical problems
• Build AWS experience through POCs
• Gain insights and early wins
re:Think Provides:
• Technical project engagement to resolve issues, identify
POCs
Objective: Large Scale Re-Platforming and Migrations
• Business outcome driven
• Systematic approach
• Joint customer and AWS commitment and investments
Database Freedom MAP Provides:
• Support to build business case
• Based upon size of the opportunity
• Training
• Professional Services or Partner technical support
• Service credits proportional to size of opportunity and
customer commitment

12. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Scope
Determine potential scope and
timelines with key stakeholders
Address questions and concerns from
technical and business stakeholders
Educate key personnel on AWS technologies
Key Activities
Analyze existing Applications/Databases for complexity and sizing
Rationalize potential re-platforming against AWS DB’s and determining
Migration effort
Provide High level timeline, effort and cost savings against existing
architecture
Outcome
Buy-in across key
stakeholders to move
forward with the DB
Freedom initiative
Resources
AWS
• DB Specialist SA’s
• ProServe/Partner
Customer
• App/DB Specialists
• Migration Lead
Database Freedom Workshop

13. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
First Call
Presentation
Replatform
Lift & Shift (RDS)
Lift & Shift
(EC2/EBS)
• Workloads selected for
feasibility assessment
(e.g., by Geography,
Function or LOB)
Opportunity
Follow-up
WQF based workload
assessment to determine
risk/effort of migrations
Key data collected for
opportunity assessment
• Sizing Information
- Number of CPU’s /
Cores
- Database Size
- IOPS
- Redundancy/
Replication
- Named/Peak Users
• Licensing Info
Assessment Deliverables
• Categorization of
workloads by migration
complexity
• Sizing of Replatform
workloads
• Proof of Concepts
recommendation
Next steps to progress
opportunity:
• Best approach based
on customer needs
• POCs as appropriate
• Option for broader
environmental
assessment via AWS
or partners
• Option for licensing
assessment via
partner
• Option for
training/project work
to build customer
capability
Total Customer
Commercial Engine
Workloads
DB Freedom “2 Day Workshop”
Workshop workload selection Technical assessment Opportunity Assessment
Set for initial
evaluation
Categorization Sizing
POCs Path forward
Customer
interest in re-
platforming
from legacy
DBs
Workshop Approach

14. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Disparate DB Workloads
Oracle EBS
PSFT / JDE
/ SAP
Siebel / CRM
DW / Lakes
Custom Apps
on Oracle DB
SQL*Server /
Other
DB’s
Big Data /
NoSQL
Outcomes
Re-Platforming
Gathering Data and Organizing
“Discovery & Planning”
Workload
Qualification
Framework
Assessment
Questionnaires
2-Day
Workshops
• Application Discovery
Aurora MySQL
Aurora PostgreSQL
DynamoDB
Redshift
Relational Database Service
Oracle
SQL Server
MySQL
PostgreSQL
Compute & Storage
Elastic Compute
Elastic Block Storage
Other Options
Simple Storage
• Migration Hub
• Migration Readiness Program
IncreasingValue
Workload Analysis

15. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
• The WQF includes self-service tools, a questionnaire, and design review guidance that Solutions Architects,
Partners and Consultants can use to classifying workloads to determine the ease of migration, staff-hour
consumption and to which appropriate AWS Service to migrate
• There are two main types of database workloads:
• Online Transaction Processing (OLTP): many small/fast transactions and queries via indexes that return
few rows
• Data Warehouse (DW): interactive and long-running queries that scan millions of rows and batched
updates
• WQF classifies OLTP and DW workloads into five categories:
Category 1 ODBC/JBDC workloads
Category 2 Light, proprietary feature workloads
Category 3 Heavy, proprietary feature workloads
Category 4 Engine-specific workloads
Category 5 Non-portable, high-risk or lift-and-shift
Workload Qualification Framework (WQF)

16. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Answered question list
Design Brief – logical architecture describing decision points and technology selections
Application & DB Categorizations
Workload sizing & parts list
Actions Register – next steps list owned by Account team
Assessment of timelines
Workshop Output

17. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Migration SI Partners License Advisory Partners
AWS Database Partners

18. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Partner Migration Program
Database Migration Partners
Funding available to support migration activities led by SI Partners who have a proven
practice in heterogeneous migrations
Funding to support Licensing Partner who can evaluate licensing compliance in
migration planning phase

19. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Take the next steps to Database Freedom
• Determine path, Project Based or Large Scale re-platforming
• If project based, determine POC workloads
• Partner or customer driven
• Schedule the onsite DB Freedom Workshop
• Workshop Pre-work / Preparation
• Workshop (2 Day Workshop)
• Workshop Summary / Findings (Sizing, Priorities, Timelines)
• Determine path to how AWS can help you move your workloads

20. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Thank You!
Ronen Amrani

21. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
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
& scalability
5x throughput of standard
MySQL and 3x of standard
PostgreSQL; scale-out up to
15 read replicas
Availability
& durability
Fault-tolerant, self-healing
storage; six copies of data
across three AZs; continuous
backup to S3
Highly secure
Network isolation,
encryption at
rest/transit
Fully managed
Managed by RDS: no
hardware provisioning,
software patching, setup,
configuration, or backups

22. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon Aurora - High Performance
Scale out to millions of reads per second
Availability
Zone 1
Scale-out read performance
Availability
Zone 2
Availability
Zone 3
Application
Read Replica
1
Read Replica
2
Master
Node
Shared distributed storage volume
Up to 15 read replicas across three AZs
Auto-scale new read replicas
Seamless recovery from read replica failures

23. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Aurora Serverless
On-demand, auto-scaling database for applications with variable workloads
Warm
Capacity Pool
Application
Database Endpoint
Scalable Database Capacity
(Compute + Memory)
Shared Distributed Storage
Starts up on demand, shuts down when not in use
Automatically scales with no instances to manage
Pay per second for the database capacity you use

24. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Aurora Multi-Master (Preview)
First relational database to scale out reads and writes across multiple data centers
Availability
Zone 1
Scale-out both reads and writes
Availability
Zone 2
Availability
Zone 3
Application
Read/Write
Master 2
Read/Write
Master 3
Read/Write
Master 1
Shared distributed storage volume
Zero application downtime from ANY instance
failure
Zero application downtime from ANY AZ failure
Faster write performance and higher scale
Sign up for single-region multi-master preview
today; multi-region multi-master coming in 2018

25. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon RDS
Managed relational database service with a choice of popular database engines
Easy to administer
No need to provision infrastructure,
install, and maintain DB software
Highly scalable
Scale DB compute and storage with
a few clicks; minimal downtime for
your application
Available & durable
Automatic Multi-AZ data replication;
automated backup, snapshots, and
failover
Fast & secure
SSD storage and
guaranteed provisioned I/O; data
encryption at rest and in transit

26. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon DynamoDB
Fully-managed nonrelational database for any scale
High performance
Fast, consistent performance
Virtually unlimited throughput
Virtually unlimited storage
Secure
Encryption at rest and transit
Fine-grained access control
PCI, HIPAA, FIPS140-2 eligible
Fully managed
Maintenance-free
Serverless
Auto scaling
Backup and restore
Global tables

27. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Many Applications Require
Millisecond Latency at Any Scale
Example: Amazon Prime Day 2017
Biggest shopping event in
Amazon history
Peaked at 12.9 million
requests per second
Thousands of Amazon
teams using DynamoDB
3.34 trillion requests

28. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
DynamoDB Backup and Restore
On-demand backups for
long-term data archiving and
compliance
Continuous backups for
point-in-time recovery
Back up PBs of data instantly
with no performance impact

29. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
DynamoDB 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
rewrites required

30. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon Redshift
10x faster at 1/10th the cost
Fast
Delivers fast results for all
types of workloads
Simple
Create and start using a data
warehouse in minutes
Cost-effective
No upfront costs, start small,
and pay as you go
Scalable
Gigabytes to petabytes
to exabytes
Integrated
Integrated with S3 data lakes,
AWS services and third-party tools
Secure
Audit everything; encrypt
data end-to-end; extensive
certification and compliance

31. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Query All Your Data
Redshift Spectrum Feature Extends Redshift Queries to an Amazon S3 Data Lake
Amazon
Redshift Spectrum
Redshift Query
Engine
Redshift Data
Data Lake
Amazon S3
Directly query exabytes in S3,
no loading required
Query across Redshift and S3
Scale compute and storage separately
High concurrency
Support for Parquet, ORC, Avro, CSV,
JSON, Grok, and other open file formats
Pay only for the amount of data scanned

32. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon Redshift
Architecture
Query
SELECT COUNT(*)
FROM S3.EXT_TABLE
GROUP BY …
Amazon
Redshift
JDBC/ODBC
AWS Glue
Data Catalog
Amazon S3
Exabyte-scale object storage
Redshift Spectrum
Scale-out serverless compute

33. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon EMR
Managed Hadoop and Spark in the cloud at 1/8th the cost
Enterprise-grade Easy Lowest cost

34. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Enterprise-grade Hadoop & Spark
Scale to any size
• Scale compute (EMR) &
storage (S3) independently
• Store, and process any
amount of data—PB to EBs
• Provision one, hundreds,
or thousands of nodes
• Auto-scaling
Data Lake
on AWS
Amazon EMR

35. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Enterprise-grade Hadoop & Spark
Highly available and durable
• S3 is designed to deliver 99.999999999% durability
• EMR monitors your cluster—replacing poorly performing
& failed nodes, and restarting services
• Monitor your clusters using Amazon CloudWatch
• Built-in console to view job history & browse logs
• EMR has on-cluster HDFS for data persistence

36. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Enterprise-grade Hadoop & Spark
Highly secure
• Encryption of data at rest and in-transit
• ML-powered security with Amazon Macie
• Network isolation using Amazon VPC
• Access and permissions control with IAM policies
• Log, and audit activity with AWS CloudTrail
• Microsoft AD integration with Kerberos support

37. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Easy
Spin up clusters in minutes
• Launch Hadoop & Spark clusters in minutes
• No need to install or maintain Hadoop
• Cluster tuning, and configuration done for you
• Latest Hadoop versions within 30 days of release

38. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Easy
Automatic and elastic scaling
• Automatically scale clusters based on policies
• Shut down cluster when processing completes
• Optimized for both transient and long-running clusters
• No manual intervention needed

39. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Lowest cost
Save 75–90% using Reserved Instances and Spot
• Commit to a set term and save up
to 75% with Reserved Instance
• Run on spare compute capacity and
save up to 90% with Spot
• Pay a fraction of on-demand price
• Name your bid price. If it exceeds
the market, you get the resource
• Provision from a list of instance types
with Spot and on-demand
• Launch in the most optimal AZ based on
capacity/price
• Spot Block support
EC2 Spot
up to
90% savings
On-demand
EC2 nodes

40. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon ElastiCache
Fully-managed, Redis or Memcached compatible, low-latency, in-memory
data store
Fully managed
AWS manages all hardware
and software setup,
configuration, monitoring
Extreme performance
In-memory data store and cache
for sub-millisecond response times
Easily scalable
Read scaling with replicas
Write and memory scaling
with sharding
Non-disruptive scaling

41. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon Neptune
Fully managed graph database
Fast & scalable
Store billions of relationships; query
with millisecond latency
Reliable
Six replicas of your data across
three AZs with full backup and
restore
Easy
Build powerful queries easily with
Gremlin and SPARQL
Open
Supports Apache TinkerPop and
W3C RDF graph models
Gremlin
SPARQL

42. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Graph Use Cases
Social news feed Recommendations Retail fraud detection
Friends
Use
Play
Like
Check in
Like
Connect
Read
Credit
card
Product
Email
address
Credit
card
Known
fraud
Uses
Paid
with
Uses
Paid
with
Paid with
Purchased
Approve
purchase?
Sport
Product
Purchased
Purchased
People
who also
follow sports
purchased…
Purchased
Knows
Knows
Do you
know…
Follows
Follows
Follows

43. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Database Migration Service
Migrating
Databases to AWS
55,000+
Databases migrated
Migrate between on-premises and AWS
Migrate between databases
Data replication for zero-downtime migration
Automated schema conversion