The document is an introduction to MongoDB, a cross-platform, open-source document-oriented database that uses JSON-like documents with dynamic schemas. It covers the features of MongoDB, including its document model, query language, and ecosystem, highlighting its flexibility and ease of use compared to traditional databases. Additionally, it discusses the importance of resiliency through replica sets and the various tools available within the MongoDB ecosystem.

2. An Introduction to Document
Databases with MongoDB
Brett Gray, Senior Consulting Engineer, MongoDB

3. Why am I here?
About a decade ago, three guys with a lot of industry experience got together and thought
“There must be a better way”. A better way to store data, that was more intuitive and more
natural…

4. Agenda
What is MongoDB?
Document Model
Query Language
Resiliency
MongoDB Ecosystem
Demo

5. Brett Gray
Senior Consulting Engineer

6. About Me
I’m a Senior Consulting Engineer in the Professional Services team at MongoDB.
In a previous life, I served on Submarines in the Royal Australian Navy and was a Principal Engineer at
Puppet…….I also have a Graduate Diploma of Brewing.

7. What is MongoDB?

8. What is MongoDB?
MongoDB is a cross-platform and open-source document-oriented general purpose database. As a document
database, MongoDB doesn’t use table-based structure, rather it uses JSON-like documents that have dynamic
schemas which it calls BSON.
Please keep in mind that NoSQL does not mean no relationships!

9. What is MongoDB?
Server written in C++ and C
Tools written in C++, C, Go, Java, and JavaScript
Binary packages are available for download at mongodb.com/downloads
Source code for the server is available at github.com/mongodb
Ready for deployment in the cloud, on VMs or on bare metal

10. What is MongoDB?
MongoDB was written to make it simple to store data.
• {"Key": "Value"}
Documents map naturally to common data structures in most popular programming languages
Schemas are dynamic. There’s no need for expensive migrations.
As new data is encountered, just store it. If the shape of data needs to change, then change it.
We are schema-flexible, but it is important to be consistent

11. What is MongoDB?
MongoDB is an ecosystem of products, including a database, visual data explorer, platform, and analytics tools to
make it easier than ever to develop your applications.

12. Document Model

13. Document Model

14. Not just key-
valueMongoDB’s document model is not just a key-value
store.
Rich document composition is possible, and
encouraged.
Store embedded objects, arrays, rich data types, and
more.
{
"title": "The Martian",
"year": 2015,
"runtime": 130,
"released": ISODate("2015-10-
02T00:00:00Z"),
"cast": [
"Kate Mara",
"Matt Damon",
"Jessica Chastain",
"Kristen Wiig"
]
}

15. Document Model
MongoDB RDBMS
Database Database
Collection Table
Index Index
Document Row
Field Column
Embedding, Linking, $lookup Join

16. …using a SQL Model

17. …using a Document Model

18. Document Model
It’s a natural way to think about data, and maps incredibly well to patterns we know and common types and
structures we use daily.
The schema should be modelled from how you access your data.
As highlighted, the schema is flexible, but you can use schema validation within in your application and within the
database to enforce your schema.

19. Query Language
MQL and Aggregation

20. Query Language
CREATE TABLE movies (
id MEDIUMINT NOT NULL
AUTO_INCREMENT,
title Varchar(30),
year Number,
rating Number,
PRIMARY KEY (id)
)
db.createCollection("movies")

21. Query Language
INSERT INTO movies(title,
year, rating) VALUES ("The
Shawshank Redemption", 10,
1994)
db.movies.insertOne({title:
"The Shawshank Redemption",
year: 1994, rating: 10})

22. Query Language
ALTER TABLE movies ADD cast
ARRAY
UPDATE movies SET cast =
["Morgan Freeman", "Tim
Robbins"] WHERE title = "The
Shawshank Redemption"
db.movies.updateOne(
{title: "The Shawshank
Redemption"},
{$set: { "cast": ["Morgan
Freeman", "Tim Robbins" ] } }
)

23. Query Language
ALTER TABLE movies ADD cast
ARRAY
UPDATE movies SET cast =
["Morgan Freeman", "Tim
Robbins"] WHERE title = "The
Shawshank Redemption"
db.movies.updateOne(
{title: "The Shawshank
Redemption"},
{$set: { "cast": ["Morgan
Freeman", "Tim Robbins" ] } }
)

24. Query Language
SELECT * FROM movies
SELECT * FROM movies WHERE
rating > 7
SELECT * FROM movies WHERE
rating > 7 LIMIT 1
SELECT * FROM movies WHERE
rating > 7 AND year > 1990
??
db.movies.find()
db.movies.find({rating: { $gt:
7 }})
db.movies.findOne({rating: {
$gt: 7 }}).limit(1)
db.movies.find({rating: { $gt:
7 }, year: { $gt: 1990 } })
db.movies.find({cast: "Morgan
Freeman"})

25. Query Language
CREATE INDEX
idx_movie_rating_desc ON
movies(rating DESC)
db.movies.createIndex({ rating:
-1 })

26. Query Language - Performance
Indexes support the efficient execution of queries in MongoDB.
Many index types
• Single Field
• Multikey
• Text
• Geospatial
• Hashed
• Compound

27. Query Language - Aggregation
A framework for data aggregation modelled on the concept of data processing pipelines.
Documents enter a multi-stage pipeline that transforms the documents into aggregated results.
Reduce the CPU cycles in processing your app, let MongoDB handle aggregation.
Results produced from aggregation lower in total byte size of your data, saving bandwidth.

28. Query Language - Aggregation
A framework for data aggregation modeled on the concept of data processing pipelines.
Documents enter a multi-stage pipeline that transforms the documents into aggregated results.

29. Query Language
Expressive
Intuitive
Logical

30. Resiliency

31. Resiliency – The Replica Set

32. Resiliency – The Replica Set
Your application talks to MongoDB through the
driver, which is constantly monitoring your replica
set health.
Internally, the replica set is monitoring health as
well, ready to react in case of emergency.

33. Resiliency - Reacting

34. Resiliency – The Replica Set
Your application talks to MongoDB through the
driver, which is constantly monitoring your replica
set health.
Internally, the replica set is monitoring health as
well, ready to react in case of emergency.

35. MongoDB Ecosystem

36. MongoDB Ecosystem
Compass
Atlas
Stitch
Charts
Ops Manager
Cloud Manager

37. Ecosystem - Compass
MongoDB’s GUI to explore and interact with your data.

38. Ecosystem - Atlas

39. Atlas – Infrastructure
Infrastructure managed by MongoDB
Updated with zero downtime
Available in AWS, GCP, and Azure

40. Atlas – Built in Security
TLS/SSL
Authentication and Authorization
IP Whitelists
User roles
VPC Peering (AWS and GCP)
AES-256 hardware encryption

41. Atlas – Graphs and Metrics
MongoDB
Hardware
Utilization
Performance

42. Atlas – Real Time Performance

43. Atlas – So Much More
Monitoring and Alerting
• Supports Third-Party integration
• Webhooks
• Email
• SMS
• PagerDuty
• Slack
Live Migration
Backups and Recovery
BI Connector

44. Ecosystem - Stitch

45. Ecosystem - Charts

46. Live Coding
Typing accuracy and mental faculty guaranteed to reduce by 37%!

47. Thank You!