1. NoSQL with ColdFusion
Using MongoDB
Indy Nagpal
CFObjective, Melbourne, 2011

2. About me

3. About me
✴ Straker Translations, New Zealand
✴ Been working with CF for a while now
✴ Cloud-based applications using Railo
✴ Love CFWheels
✴ nagpals.com/blog, @indynagpal

4. NoSQL?

5. NoSQL?
✴ Different things to different people
✴ Non-Relational rather than NoSQL
✴ System for storage/retrieval of data
✴ Persistence layer is not a responsibility of a
single system

6. Why NoSQL?

7. Why NoSQL?
✴ 100s of millions of items in a big table

8. Why NoSQL?
✴ 100s of millions of items in a big table
✴ Dynamic data structure

10. SQL NoSQL
Static Data Structure Dynamic Data Structure
Dynamic Query Static Query (generally)
Consistency Eventual consistency
Transactions Limited Transactions
Difficult to distribute Distributed, fault-tolerant
Limited performance under load Optimized for heavy read-write

11. SQL NoSQL
Static Data Structure Dynamic Data Structure
Dynamic Query Static Query (generally)
Consistency Eventual consistency
Transactions Limited Transactions
Difficult to distribute Distributed, fault-tolerant
Limited performance under load Optimized for heavy read-write

12. SQL NoSQL
Static Data Structure Dynamic Data Structure
Dynamic Query Static Query (generally)
Consistency Eventual consistency
Transactions Limited Transactions
Difficult to distribute Distributed, fault-tolerant
Limited performance under load Optimized for heavy read-write

13. SQL NoSQL
Static Data Structure Dynamic Data Structure
Dynamic Query Static Query (generally)
Consistency Eventual consistency
Transactions Limited Transactions
Difficult to distribute Distributed, fault-tolerant
Limited performance under load Optimized for heavy read-write

14. SQL NoSQL
Static Data Structure Dynamic Data Structure
Dynamic Query Static Query (generally)
Consistency Eventual consistency
Transactions Limited Transactions
Difficult to distribute Distributed, fault-tolerant
Limited performance under load Optimized for heavy read-write

15. SQL NoSQL
Static Data Structure Dynamic Data Structure
Dynamic Query Static Query (generally)
Consistency Eventual consistency
Transactions Limited Transactions
Difficult to distribute Distributed, fault-tolerant
Limited performance under load Optimized for heavy read-write

16. SQL NoSQL
Static Data Structure Dynamic Data Structure
Dynamic Query Static Query (generally)
Consistency Eventual consistency
Transactions Limited Transactions
Difficult to distribute Distributed, fault-tolerant
Limited performance under load Optimized for heavy read-write

17. NoSQL DBs

18. NoSQL DBs
✴ Used with CF
✴ Apache CouchDB
✴ MongoDB
✴ Amazon SimpleDB
✴ CF/Java Wrappers available

19. What is MongoDB

20. What is MongoDB
✴ A Document-oriented database
✴ “Humongous”
✴ Scalable, high-performance, open-source
✴ An alternative to relational databases
✴ One of the NoSQL technologies

21. Key Difference

22. Key Difference
✴ Most No-SQL databases
✴ dynamic data
✴ static queries
✴ MongoDB
✴ dynamic data
✴ dynamic and static queries

23. Basic Concepts

24. Basic Concepts
✴ Database

25. Basic Concepts
✴ Database
✴ Collections (broadly like table)

26. Basic Concepts
✴ Database
✴ Collections (broadly like table)
✴ Documents (like row)

27. Basic Concepts
✴ Database
✴ Collections (broadly like table)
✴ Documents (like row)
✴ Fields (like columns)

28. Basic Concepts
✴ Database
✴ Collections (broadly like table)
✴ Documents (like row)
✴ Fields (like columns)
✴ Collections are indexed

29. Basic Concepts
✴ Database
✴ Collections (broadly like table)
✴ Documents (like row)
✴ Fields (like columns)
✴ Collections are indexed
✴ Cursors (retrieve data as required)

30. Concepts

31. Concepts
✴ New terminology
✴ Similar ideas, but not identical
✴ RDBMS - columns defined for tables
✴ NoSQL - fields defined for documents
✴ Collections are more like containers

32. Drivers

33. Drivers
✴ Officially supported drivers
✴ Language-specific drivers (Java, Ruby, etc.)
✴ Framework-specific (MongoMapper)
✴ Wrappers built on top of drivers
✴ cfmongodb built on Java drivers
✴ Unlike Apache CouchDB that uses REST

34. BSON

35. BSON
✴ Binary JSON format
✴ Supports embedding of documents and
arrays within other documents and arrays
✴ Lightweight
✴ Traversable
✴ Efficient
✴ bsonspec.org

36. CF and Mongo

37. CF and Mongo
✴ cfmongodb (on Github) -- excellent
✴ Wrapper around Java drivers
✴ Most functionality encapsulated
✴ Inserts, updates, delete, find
✴ Map-reduce, Geospatial

38. CF and BSON
• Structs/arrays persisted as they are!
people = mongo.getDBCollection(“people”)
person = {
“fname” : “John”,
“lname” : “Doe”
}
people.save(person)

39. Init

40. Init
mongoConfig = createObject(
'component',
'cfmongodb.core.MongoConfig').init(dbName="test")

41. Init
mongoConfig = createObject(
'component',
'cfmongodb.core.MongoConfig').init(dbName="test")
mongo = createObject('component',
'cfmongodb.core.Mongo').init(mongoConfig)

42. Init
mongoConfig = createObject(
'component',
'cfmongodb.core.MongoConfig').init(dbName="test")
mongo = createObject('component',
'cfmongodb.core.Mongo').init(mongoConfig)
people = mongo.getDBCollection('people')

43. Add Data

44. Add Data
// create some data
newPeople = []

45. Add Data
// create some data
newPeople = []
arrayAppend(newPeople, {‘fname’: ‘John’, ‘email’ : ‘john@doe.com’})

46. Add Data
// create some data
newPeople = []
arrayAppend(newPeople, {‘fname’: ‘John’, ‘email’ : ‘john@doe.com’})
arrayAppend(newPeople, {‘fname’: ‘Jane’, ‘lname’ : ‘Doe’})

47. Add Data
// create some data
newPeople = []
arrayAppend(newPeople, {‘fname’: ‘John’, ‘email’ : ‘john@doe.com’})
arrayAppend(newPeople, {‘fname’: ‘Jane’, ‘lname’ : ‘Doe’})
// save everything at once
people.saveAll(newPeople)

48. Find / Update

49. Find / Update
person = people.query().$eq("fname", "Jane").find()

50. Find / Update
person = people.query().$eq("fname", "Jane").find()
// update a record
person[“email”] = “jane@doe.com”
person.update(person)

51. Tools

52. Tools
✴ Terminal console
✴ MongoHub (Mac)
✴ MongoExplorer, MongoVision (Windows)
✴ SSH Tunnel to connect
✴ mongohq.com (hosted MongoDB/admin)

53. MongoDB and Railo

54. MongoDB and Railo
✴ Railo Extension
✴ Cache CF variables/data
✴ Store key-value pairs
✴ cacheGet()
✴ cachePut()

55. Queries and Map-
reduce

56. Queries and Map-
reduce
✴ Queries - rapid development
✴ Map-reduce - advanced querying
✴ Query and Map-reduce together give
MongoDB an edge over other NoSQL
alternatives

57. Data Modeling

58. Data Modeling
✴ No Joins! Scary?
✴ Embedding documents supported via ID
✴ Big mind shift
✴ ‘Fear’ of duplicate data drives design
decisions in relational db world

59. CF ORM

60. CF ORM
✴ No support in CF ORM frameworks
✴ Other language frameworks more
advanced
✴ Ruby on Rails - mongomapper
✴ Need ORM integration for wider adoption

61. Asynchronous

62. Asynchronous
✴ Asynchronous inserts/updates
✴ Journaled
✴ Capped Collections (FIFO)

63. Time taken to add 20,000 records with 5 words in each record
30
25
Time in Seconds
20
15
10
5
0
mysql (cfquery) filesystem (cflog) mongodb (cfmongodb)

64. Compelling features

65. Compelling features
✴ On-demand database and collection
creation
✴ Asynchronous writes
✴ Replication - simple and easy
✴ Large-scale data processing
✴ Sharding - horizontal scaling
✴ Geospatial indexes

66. When to use?

67. When to use?
✴ Relational DBs suffice for most projects
✴ Abstraction via ORM is very useful
✴ MongoDB -- alternative/add-on
✴ Removes reliance on only one data storage
mechanism

68. Learning Curve

69. Learning Curve
✴ Syntax
✴ Concepts like sharding, replication
✴ Well-documented / blogged
✴ Active mailing list
✴ Being used in production

70. So...

71. So...
✴ Another tool to have in one’s kit
✴ Extremely useful and easy to use
✴ Worth spending some time on

72. Thank you!
@indynagpal
indy@nagpals.com
http://nagpals.com/blog