This webinar will guide you through the best practices for migrating off of a relational database. Whether you are migrating an existing application, or considering using MongoDB in place of your traditional relational database for a new project, this webinar will get you to production faster, with less effort, cost and risk.

1. “Ditch Oracle Now”
Migration Best Practices
Mat Keep
MongoDB Product Team
mat.keep@mongodb.com
@matkeep

3. Migrations & New Apps
UK Public Sector Agencies Ahead of the “Edict”

4. Migration is Rarely Just Cost-Driven…..
Enabling New &
Evolving Existing Apps
Transforming Customer Experience
Lowering TCOInnovating Faster than Competitors
€

5. 5
Relational Database Challenges
Data Types
Unstructured data
Semi-structured data
Polymorphic data
Agile Development
Iterative
Short development
cycles
New workloads
Volume of Data
Petabytes of data
Trillions of records
Millions of queries/sec
New Architectures
Horizontal scaling
Commodity servers
Cloud computing

6. 6
Expressive
Query
Language
Strong
Consistency
Secondary
Indexes
Flexibility
Scalability
Performance
Relational

7. 7
NoSQL
Expressive
Query
Language
Strong
Consistency
Secondary
Indexes
Flexibility
Scalability
Performance

8. 8
Expressive
Query
Language
Strong
Consistency
Secondary
Indexes
Flexibility
Scalability
Performance
Nexus Architecture

9. 9
• Migration Roadmap
• Schema Design
• Application Integration
• Data Migration
• Operational Considerations
• Resources to Get Started
What We’ll Cover

10. Migration Steps

11. Migration Roadmap
• Backed by Free, Online MongoDB Training
• 350k+ registrations to date
• Consulting and Support also available

12. Schema Design

13. Definitions
RDBMS MongoDB
Database Database
Table Collection
Row Document
Index Index
JOIN Embedded Document
or Reference

14. Data Models: Relational to Document
Relational MongoDB
{
first_name: ‘Paul’,
surname: ‘Miller’,
city: ‘London’,
location:
[45.123,47.232],
cars: [
{ model: ‘Bentley’,
year: 1973,
value: 100000, … },
{ model: ‘Rolls Royce’,
year: 1965,
value: 330000, … }
]
}

15. 15
Anatomy of a BSON Document
{
first_name: ‘Paul’,
surname: ‘Miller’,
cell: ‘+447557505611’
city: ‘London’,
location: [45.123,47.232],
Profession: [banking, finance,
trader],
cars: [
{ model: ‘Bentley’,
year: 1973,
value: 100000, … },
{ model: ‘Rolls Royce’,
year: 1965,
value: 330000, … }
]
}
Fields can contain an array of
sub-documents
Fields
Typed field values
Fields can
contain
arrays

16. 16
RDBMS
Document Model Benefits
MongoDB
{
_id : ObjectId("4c4ba5e5e8aabf3"),
employee_name: "Dunham, Justin",
department : "Marketing",
title : "Product Manager, Web",
report_up: "Neray, Graham",
pay_band: “C",
benefits : [
{ type : "Health",
plan : "PPO Plus" },
{ type : "Dental",
plan : "Standard" }
]
}

17. 17
An Example

18. 18
Defining the Data Model
Application RDBMS Action MongoDB Action
Create Product Record INSERT to (n) tables
(product description, price,
manufacturer, etc.)
insert() to 1 document
with sub-documents,
arrays
Display Product Record SELECT and JOIN (n)
product tables
find() aggregated
document
Add Product Review INSERT to “review” table,
foreign key to product
record
insert() to “review”
collection, reference to
product document
More actions….. …… ……
• Analyze data access patterns of the application
– Identify data that is accessed together, model within a
document
• Identify most common queries from logs

19. 19
• Embedding
– For 1:1 or 1:Many (where “many” viewed with the parent)
– Ownership and containment
– Document limit of 16MB, consider document growth
– Atomicity of updates
• Referencing
– _id field is referenced in the related document
– Application runs 2nd query to retrieve the data
– Data duplication vs performance gain
– Object referenced by many different sources
– Models complex Many : Many & hierarchical structures
Modeling Relationships:
Embedding and Referencing

20. Referencing Publisher ID in Book
 publisher = {
 _id: "oreilly",
 name: "O’Reilly Media",
 founded: "1980",
 location: "CA"
 }
 book = {
 title: "MongoDB: The Definitive Guide",
 authors: [ "Kristina Chodorow", "Mike Dirolf" ],
 published_date: ISODate("2010-09-24"),
 pages: 216,
 language: "English",
 publisher_id: "oreilly"
 }

21. Further Reading
http://docs.mongodb.org/manual/data-modeling/

22. 22
• MongoDB indexing will be familiar to DBAs
– B-Tree Indexes, Secondary Indexes
• Single biggest tunable performance factor
– Define indexes by identifying common queries
– Use MongoDB explain to ensure index coverage
– MongoDB profiler logs all slow queries
Indexing in MongoDB
• Compound
• Unique
• Array
• TTL
• Geospatial
• Hash
• Sparse
• Text Search

23. Application Integration

24. Drivers & Ecosystem
Morphia
MEAN Stack
Python PerlRuby
Support for the most popular languages and frameworks

25. Mapping MongoDB Query Language to SQL
Mapping Chart:
http://docs.mongodb.org/manual/reference/sql-comparison/

26. 26
• Ad-hoc reporting, grouping and aggregations, without the
complexity of MapReduce
– Max, Min, Averages, Sum, Union, Redact, GeoNear
• Similar functionality to SQL GROUP_BY
• Processes a stream of documents
• Series of operators
– Filter or transform data
– Input/output chain
• Supports single servers & shards
Application Integration
MongoDBAggregation Framework

27. SQL to Aggregation Mapping
Mapping Chart:
http://docs.mongodb.org/manual/reference/sql-aggregation-comparison/

28. 28
BI Integration

29. Data Integrity

30. Document Level ACID Compliance
• “All or Nothing” updates
• Extends to embedded documents
and arrays
• Consistent view to application
• Transaction-like semantics for
multi-doc updates with
findandmodify() or 2PC
{
first_name: ‘Paul’,
surname: ‘Miller’,
city: ‘London’,
location:
[45.123,47.232],
cars: [
{ model: ‘Bentley’,
year: 1973,
value: 100000, … },
{ model: ‘Rolls Royce’,
year: 1965,
value: 330000, … }
]
}

31. 31
Maintaining Strong Consistency
• By default, all reads and writes sent
to Primary
• Reads to secondary replicas will be
eventually consistent
• Scale by sharding
• Read Preferences control how
reads are routed

32. Data Durability: Single Node & Multi-Node
• Journaling by default
• Write Concerns Give
More Guarantees
• Configurable per
operation

33. Migration and
Operations

34. 34
Traditional ETL
Source Database ETL

35. Incremental Migration, Live
Legacy
Database
MongoDB
Database

36. 36
• Configuration, Provisioning, Monitoring and Backup
• High Availability & Disaster Recovery
• Scalability
• Hardware selection
– Commodity Servers: Prioritize RAM, Fast CPUs & SSD
• Security
– Access Control, Authentication, Encryption
Operations
Download the Whitepaper
MongoDB Operations Best Practices

37. High Availability: Replica Sets
Replica Set – 2 to 50 copies
Self-healing shard
Data Center Aware
Addresses availability considerations:
High Availability
Disaster Recovery
Maintenance
Workload Isolation: operational & analytics

38. 38
Scalability: Auto-Sharding
Multiple query optimization models
Each sharding option appropriate
for different apps
Elastic and self-balancing
Shard Key Selection:
http://docs.mongodb.org/manual/tutorial/choose-a-shard-key/

39. 39
Ops Manager & Cloud Manager
Single-click provisioning, scaling &
upgrades, admin tasks
Monitoring, with charts, dashboards and
alerts on 100+ metrics
Backup and restore, with point-in-time
recovery, support for sharded clusters
The Best Way to Manage MongoDB
Up to 95% Reduction in Operational Overhead

40. Getting Started

41. MongoDB Enablement
Consulting, training, and professional services
throughout your project lifecycle
Design &
Development
Rapid Start
Database
Modernization
Private Training
Test / QA
Production
Readiness
Prototype T&M
Pre-Production
Performance
Evaluation &
Tuning
Health Check
Production &
Expansion
Ops Optimization
Training for
Expanded Team

42. 42
Enablement:
Database
Modernization
Receive a thorough
assessment of whether
MongoDB will better support
your application than your
current database
Deliverables
A summary of your application
requirements
The results of the fit assessment
If applicable, recommendations for a
migration to MongoDB, including an
estimation of the effort required
Details
A MongoDB consulting engineer will
spend at least 3 consecutive days
working with your team, typically on
site
Within 10 business days, the
MongoDB consulting engineer will
deliver to you a comprehensive
written report

43. 43
MongoDB
Enterprise
Advanced
The best way to run MongoDB
Supported.
Secured.
Certified.
What’s included?
24 x 7 Support
Ops Manager
Advanced Security
Commercial License
Platform Certification
On-Demand Training
Free for evaluation & development
https://www.mongodb.com/lp/download/
mongodb-enterprise

44. 44
• Benefits of migration are well understood
• Many successful projects
• Largest differences in data model and query
language
– Invest time in schema design…don’t think in tables!
• Many principles of RDBMS apply to MongoDB
Summary
Download the Guide
https://www.mongodb.com/collateral/rdbms-mongodb-migration-guide

45. http://cl.jroo.me/z3/v/D/C/e/a.baa-Too-many-bicycles-on-the-van.jpg
Questions?
@matkeep
mat.keep@mongodb.com

47. Migration in Action
Content Management
• Migration from Oracle
• Open APIs to federate
access to data
• Introduced search to
allow content discovery
• Lower latency
• Faster dev cycles
Subscriber Data Mgmt
• Migration from Oracle
• 4x faster time to market
• 50% reduction in
development costs
• 67% reduction in storage
costs
• 10x reduction in latency
Customer Data Mgmt &
Analytics
• RDBMS Migration
• 95% faster in identifying
matches
• 50% increase in paying
subscribers
• 60% increase in unique
web site visits.