You can significantly reduce database licensing and operational costs by migrating from commercial database engines to Amazon RDS. In addition, you can gain flexibility and operational efficiency by avoiding the frustrating usage constraints that accompany commercial database licenses. Amazon RDS is a fully managed database service, so you no longer need to worry about complex database management tasks. Launch a single database instance or thousands of them in just a few minutes, and pay only for what you use. Learn how AWS Database Migration Service and AWS Schema Conversion Tool help you migrate commercial databases like Oracle and Microsoft SQL Server to Amazon RDS and Aurora easily and securely with minimal downtime.

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AWS re:Invent
Best Practices for Migrating from Oracle
and SQL Server to Amazon RDS
K e v i n J e r n i g a n , S e n i o r P r o d u c t M a n a g e r , A u r o r a P o s t g r e S Q L
J o h n W i n f o r d , S e n i o r T e c h n i c a l P r o d u c t M a n a g e r , D a t a b a s e S e r v i c e s
D A T 3 0 9
N o v e m b e r 2 7 , 2 0 1 7

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Agenda
• Why migrate to Amazon RDS?
• Homogeneous migrations
• Migrating to open source: MySQL and PostgreSQL
• Amazon Aurora
• Doing the work: database migration
• Conclusion

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Migrating databases to AWS

4. Why migrate databases to the cloud?
Reduce costs
Simplify operations
Increase flexibility and possibilities

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Amazon RDS—an introduction
A managed database platform
• Multi-engine support: Amazon Aurora, MySQL,
MariaDB, PostgreSQL, Oracle, SQL Server
• Automated provisioning, patching, scaling,
backup/restore, failover
• High availability with Amazon RDS Multi-AZ

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Why migrate to Amazon RDS?
Power, HVAC, net
Rack & stack
Server maintenance
OS patches
DB s/w patches
Database backups
Scaling
High availability
DB s/w installs
OS installation
you
App optimization

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Why migrate to Amazon RDS?
OS patches
DB s/w patches
Database backups
Scaling
High availability
DB s/w installs
you
App optimization
Power, HVAC, net
Rack & stack
Server maintenance
OS installation

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Why migrate to Amazon RDS?
you
App optimization
Power, HVAC, net
Rack & stack
Server maintenance
OS patches
DB s/w patches
Database backups
High availability
DB s/w installs
OS installation
Scaling

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Homogeneous migrations

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Homogeneous migrations
If you’re not switching engines and can take downtime:
- SQL Server: bak file import
- Oracle: SQL Developer, Data Pump, Export/Import
- MySQL: read replicas
- PostgreSQL: pg_dump

11. Why use RDS for Microsoft
and Oracle Databases?
• Speed of provisioning, secure, fully managed Amazon RDS
experience
• Single-click high availability, easy scaling
• Broad set of engine features supported
• Flexible licensing models
• Bring your own license (BYOL)
• License included (LI)
• SQL Server Express, Web, Standard & Enterprise editions
supported—2014, 2016, and 2017
• Oracle Standard and Enterprise Editions

12. Amazon RDS for Oracle
Recently shipped features
• OEM Agent 13c
• Oracle Spatial/Locator/Multimedia
• Customer-initiated snapshot upgrade
• Support for APEX 5.0
• R4, t2.xlarge, t2.2xlarge, and m4.16xlarge instances
• Support for up to 16 TB of storage per instance

13. Amazon RDS for SQL Server
Recently shipped features
• Support for forced SSL
• HIPAA BAA inclusion
• Region expansion for Enterprise Edition License included
• Storage scaling up to 16 TB
• SQL Server 2017 support
• R4 and m4.16xlarge instances
• Storage reconfiguration on snapshot restore

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Migrating to open-source databases

15. Why migrate from Oracle or SQL Server
to open source?
Simplicity and innovations of open source
Lower cost and no licensing
Reduce uncertainty
Compatibility between Oracle/SQL Server
and PostgreSQL

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A brief history of MySQL
• World’s most commonly used relational database
• Key component of the LAMP open-source web application software stack
• Used in open source applications such as WordPress, Joomla, Redmine, and Drupal
• History
• First released in 1995 in Sweden by MySQL AB
• Acquired by Sun in 2008
• Launched as first Amazon RDS engine in 2009
• Acquired by Oracle in 2010
• Popular branches
• MySQL Community Edition
• MySQL Enterprise Edition
• MariaDB Server
• Percona Server
• Amazon Aurora MySQL
Amazon RDS

17.  Open-source database
 In active development for 20 years
 Owned by a foundation, not a single company
 Permissive innovation-friendly open-source license
 High performance out of the box
 Object-oriented and ANSI-SQL:2008-compatible
 Most geospatial features of any open-source database
 Supports stored procedures in 12 languages (Java, Perl, Python,
Ruby, Tcl, C/C++, its own Oracle-like PL/pgSQL, etc.)
 Most Oracle-compatible open-source database
 Highest AWS Schema Conversion Tool automatic conversion rates
are from Oracle to PostgreSQL
PostgreSQL fast facts
Open Source Initiative

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Amazon Aurora

19. A service-oriented architecture
applied to the database
Move the logging and storage layer into a
multitenant, scale-out, database-optimized
storage service
Integrate with other AWS services like
Amazon EC2, Amazon VPC, Amazon
DynamoDB, Amazon SWF, and Amazon
Route 53 for control and monitoring
Make it a managed service—using Amazon
RDS; takes care of management and
administrative functions
Amazon
DynamoDB
Amazon SWF
Amazon Route 53
Logging + Storage
SQL
Transactions
Caching
Amazon S3
1
2
3
Amazon RDS

20. Scale-out, distributed, log-structured storage
Master Replica Replica Replica
Availability Zone 1
Shared Storage Volume – Transaction Aware
Primary
Database
Node
Read
Replica /
Secondary
Node
Read
Replica /
Secondary
Node
Read
Replica /
Secondary
Node
Availability Zone 2 Availability Zone 3
AWS Region
Storage
Monitoring
Database and
Instance
Monitoring

21. Amazon Aurora storage engine overview
Data is replicated six times across three Availability
Zones
Continuous backup to Amazon S3
(built for 11 9s of durability)
Continuous monitoring of nodes and disks for repair
10 GB segments as unit of repair or hotspot rebalance
Quorum system for read/write; latency-tolerant
Quorum membership changes do not stall writes
Storage volume automatically grows up to 64 TB
AZ 1 AZ 2 AZ 3
Amazon S3
Database
Node
Storage
Node
Storage
Node
Storage
Node
Storage
Node
Storage
Node
Storage
Node
Storage
Monitoring

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Database migration

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DB migration is part of the cloud journey
How quickly and easily can I migrate my on-premises data to the cloud?
How can I minimize application downtime during database migration?
Are there ways to automate schema conversion and conflict analysis?
How can my databases be merged or modularized during the migration for data
consolidation and application refactoring?
Can I migrate off commercial databases?

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What are AWS DMS and AWS SCT?
AWS Database Migration Service (AWS DMS) easily and
securely migrate and/or replicate your databases and data
warehouses to AWS
AWS Schema Conversion Tool (AWS SCT) convert your commercial
database and data warehouse schemas to open-source engines or
AWS-native services, such as Amazon Aurora and Amazon Redshift
We have migrated over 45,000 unique databases—and counting…

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When should I use it?

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When to use AWS DMS and AWS SCT?
Modernize Migrate Replicate
Modernize your database tier
• Commercial to open-source
• Commercial to Amazon Aurora
Modernize your data warehouse –
• Commercial to Amazon Redshift
• Migrate business-critical applications
• Migrate from Classic to Amazon VPC
• Migrate data warehouse to
Amazon Redshift
• Upgrade to a minor version
• Consolidate shards into
Amazon Aurora
• Create cross-regions Read Replicas
• Run your analytics in the cloud
• Keep your dev/test and production
environment in sync

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When to use AWS DMS
Migrate databases Migrate business-critical applications
Migrate from Classic to Amazon VPC
Migrate data warehouse to Amazon Redshift
Upgrade to a minor version
Consolidate shards into Amazon Aurora
Migrate from NoSQL to SQL, SQL
to NoSQL or NoSQL to NoSQL
Amazon S3
Amazon Dynamo
DB
Amazon
Redshift
Amazon S3
Amazon
Aurora
Sources
Targets

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When to use AWS SCT
Convert schemas
Migrate warehouses
Convert database schemas
Optimize data warehouse
Migrate data warehouses to Amazon Redshift
Mass migration using AWS Snowball
DB Schema
Data Warehouses

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Why use AWS DMS and AWS SCT?
Secure
Cost-Effective
Remove Barriers
to Entry
Allow DB
Freedom
Keep a Leg in
the Cloud
Easy to Use, but
Sophisticated…
Near-Zero
Downtime

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How does it work?

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Database migration process
Source
Oracle Database on-premises
in Amazon EC2 or Amazon RDS
Source
Oracle Database on-premises
in Amazon EC2 or Amazon RDS
AWS Schema Conversion Tool
Target
Amazon Aurora PostgreSQL
Target
Amazon Aurora PostgreSQL
Step 1
Step 2
AWS Database Migration Service

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AWS Schema Conversion Tool (AWS SCT)
Features
Converting database schema
Converting data warehouse schema
Converting application SQL
Code browser that highlights places where
manual edits are required
Secure connections to your databases with SSL
The AWS Schema Conversion Tool helps automate many
database schema and code conversion tasks when
migrating from source to target database engines

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Database migration assessment
Connect AWS SCT to
source and target
databases
Run assessment report
Read executive
summary
Follow detailed
instructions

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Components of the AWS SCT console
1. Source schema
2. Action items
3. Target schema
4. Schema element details
5. Edit window

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Customer
premises
Application users
AWS
Internet
VPN
Keep your apps running during the migration
 Start a replication instance
 Connect to source and target
databases
 Select tables, schemas, or
databases
 Let AWS DMS create tables, load
data, and keep them in sync
 Switch applications over to the
target at your convenience
AWS
DMS

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Change data capture (CDC) and apply
Replication instance
Target
Transactions
Change apply after bulk load
t1
t2
Source
t1 t2
Update

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Demo

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Things to consider

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Native replication
 Your target supports native
replication
 You need to move all the data
 You don’t need any
transformation
 Your target is a new database
Dump/Restore
 You don’t have a huge database
(actually you have a small
database)
 You can take a downtime which
is bigger than the time to dump
and restore
 You will need all the data
 You will not transform schema
or data
AWS DMS and AWS SCT
 You are switching database
engines
 You need to convert your
schema
 You cannot afford downtime
 The data is so large you need
AWS Snowball
Migration methodology

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Migration is a multiphase process
Phase Description Automation Effort (%)
1 Assessment SCT 2
2 Database Schema Conversion SCT/DMS 14
3 Application Conversion/Remediation SCT 25
4 Scripts Conversion SCT 7
5 Integration with third-party applications 3
6 Data Migration DMS 4
7 Functional testing of the entire system 29
8 Performance tuning SCT 2
9 Integration and deployment 7
10 Training and knowledge 2
11 Documentation and version control 2
12 Post-production support 3

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Understand your environment
Your database
 What is the size of your database? Any large tables?
 How many schemas and tables do you have?
 What are the transaction boundaries?
 Unique data types to consider?
 Do you have LOBs in your tables, and how big are they?
 How hot is your source database?
And your network
 How to access your database (firewalls, tunnels, VPNs)
 Do you understand VPCs?
 Which security group should be used?
 Do you have enough bandwidth to move all your data?

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What affects speed?
 The size of the source database and the associated activity
 The size of the target
 Availability of bandwidth
 Replication instance size
 Schema breakdown (a single large table can slow things down)
 LOBs in the schema
 Big transactions

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Find the right people Start small Ramp up
Other considerations

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Other best practices
• Keep backups disabled during the migration
• Set up parameter group for each instance to set
parameters per-instance
• Use AWS SCT to classify databases based on level of
work to convert

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Other best practices for PostgreSQL
Use lowercase for DB object names
• Oracle by default saves everything in UPPERCASE
and PostgreSQL by default saves everything in
LOWERCASE
• Convert all the object names to lowercase in
PostgreSQL
• AWS SCT does this by default while migrating
objects from Oracle to PostgreSQL
• Lowercase names help to avoid object reference
complications

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Other best practices for PostgreSQL
• Cutover planning
• Downtime window to stop writes on Oracle and
change configs to make PostgreSQL the new data
source
• Enable all user triggers in PostgreSQL after stopping
replication and before connecting users
• Pre-cutover validation steps
• Post-cutover validation steps
• Rollback strategy
• Use log_fdw, pg_repack, and pg_audit post-cutover

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Thank you!