The document is a presentation by Glynn Bird, a Developer Advocate at IBM, focusing on NoSQL database systems as alternatives to traditional SQL RDBMS. It covers the differences between SQL and NoSQL, the types of NoSQL databases, scalability, querying, and data modeling, along with various applications such as search services and geo-spatial data. The presentation also emphasizes the ease of scaling NoSQL databases, their benefits for big data use cases, and the importance of replication for maintaining data integrity.

1. Glynn Bird – Developer Advocate – IBM Cloud Data Services
NoSQL for SQL users

2. Introduction
@glynn_bird glynn.bird@uk.ibm.com
Glynn Bird
Developer Advocate
IBM Cloud Data Services
http://www.glynnbird.com

3. Agenda
 NoSQL vs SQL
 Types of NoSQL
 Scaling
 Querying and Data Modelling
 Replication
 Demo
3

4. SQL vs NoSQL

5. RDBMs
 Relational Database Management Systems
 SQL language developed by IBM in the 1970s
 RDBMs power lots of IT systems
 Oracle, IBM DB2, MySQL, PostgreSQL etc
5

6. RDBMS downsides
 scalability
 availability
 price
6

7. NoSQL
 NoSQL = "Not only SQL"
 Response to use-cases that a RDBMS is not a good fit
 Easier to scale
7

8. 8
Key-Value Document
BigTable Graph

9. Development Cycle

10. SQL vs NoSQL - Development Cycle
 Build
 Migrate staging database
 Test
 Migrate production
 Deploy
10
 Build
 Test
 Deploy

11. Database migrations are costly
 Adding/updating/deleting columns
 May cause interruption to service
 Often performed "out of hours"
 Have to be carefully planned in multi-server deployments
11

12. Scalability

13. Scaling a web application
13

14. Scaling a SQL database
14

15. Scaling a Cloudant database
15
• Database-as-a-Service
• Free/PAYG/Dedicated/Local
• Sign up and start using
• Scale by adding nodes
• More data
• More concurrency

16. Scaling other NoSQL databases
16

17. Querying

18. SQL Tables
18
users socialmediaprofiles
userid*
firstname
lastname
registration_date
dob
address1
.
socmedid*
userid *
socmed_type
url
profile

19. SQL
19
SELECT * from users
LEFT JOIN socialmediaprofiles
ON users.userid =
socialmediaprofiles.userid
WHERE registration_date > "2015-01-01"
AND verified = true
AND socialmedia = true
ORDER BY registration_date

20. NoSQL Data model
20
{
"firstname": "Glynn",
"lastname": "Bird",
"dob": "1986-10-02",
"registration_date": "2015-02-04",
"verified": true,
"address": { "address1": "10", "postcode": "W1A 1AA" },
"socialmedia": [
{ "type": "twitter", "handle": "glynn_bird" },
{ "type": "github", "username": "glynnbird" }
]

21. Cloudant Query
21
{
"selector": {
"$and": [
{ "registration_date" : { "$gt" : "2015-01-01" } },
{ "verified" : true },
{ "socialmedia" : true}
]
},
"sort": [
"registration_date:string"
]
}

22. MapReduce
22
function(doc) {
if (doc.verified && doc.socialmedia.length > 0) {
emit(doc.registration_date, null);
}
}

23. MapReduce
23
function(doc) {
if (doc.verified && doc.socialmedia.length > 0) {
emit(doc.registration_date, null);
}
}

24. 24
CRUD – Document Primary
Index
Secondary Index
(view)
Search
Index
GeoSpatial Index Cloudant
Query
• Direct document
look up by _id
• Exists “OOTB”
• stored in a b-tree
• Primary key 
doc._id
• Built using
MapReduce
• stored in a b-tree
• Key  user-
defined field(s)
• Built using Lucene
• FTI: Any or all
fields can be
indexed
• stored in R*, TPR,
KD tree
• Lat/Long
coorindates in
GeoJSON
• “Mongo-style”
querying
• Built natively in
erlang
• Use when you
want a single
document and
can find by its _id
• Use when you can
find documents
based on their _id
• Pull back a range
of keys
• Use when you
need to analyze
data or get a
range of keys
• Ex: count data
fields,
sum/average
numeric results,
advanced stats,
group by date,
etc.
• Ad-hoc queries
• Find documents
based on their
contents
• Can do groups,
facets, and basic
geo queries (bbox
& sort by
distance)
• Complex
geometries
(polygon,
circularstring, etc.)
• Advanced
relations
(intersect,
overlaps, etc.)
• Ad-hoc queries
• Lots of operators
(>, <, IN, OR,
AND, etc.)
• Intuitive for people
coming from
Mongo or SQL
backgrounds

25. Replication

26. Cloudant Replication
26
• Replicate data from one cluster to another
• Replicate data to browser/mobile and back
• No data loss
• Offline-first apps/websites
• http://www.glynnbird.com/

27. Simple Search Service

28. Simple Search Service
 Free, open-source Bluemix App – install
with one click
 Upload your .csv or .tsv
– Imports data into Cloudant
– Indexes everything for search
– Presents HTTP Search API
 Demo!
28
https://developer.ibm.com/clouddataservices/simple-search-service/

29. Simple Search Service Architecture
29

30. Simple Search Service – Production Architecture
30

31. Cloudant use-cases
 Big Data – Large data sets
 Scalable operational data store
 Search – faceted, full-text search
 Geo-spatial – geographic, GIS systems, GeoJSON
 Offline-first – replicating data to mobile devices
31

32. Glynn Bird
Developer Advocate, Cloud Data Services
glynn.bird@uk.ibm.com
@glynn_bird
github.com/glynnbird
www.glynnbird.com