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MongoDB Making Government Better Faster Smarter Will LaForest Senior Director, MongoDB Federal [email protected] @WLaForest

Webinar: How MongoDB is making Government Better, Faster, Smarter

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Page 1: Webinar: How MongoDB is making Government Better, Faster, Smarter

MongoDB Making Government Better Faster Smarter

Will LaForestSenior Director, MongoDB [email protected]@WLaForest

Page 2: Webinar: How MongoDB is making Government Better, Faster, Smarter

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Don’t Need All 3 Vs to be Big DataDon’t Need All 3 Vs to be Big Data

Patient Records (volume, variety) PGD/Crowd Sourcing (variety)

Cyber (volume, velocity, variety)Asset Management (variety, velocity)

Page 3: Webinar: How MongoDB is making Government Better, Faster, Smarter

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Government Challenges

Many New Missions Citizen Expectations

Do More With LessFaster Time to Mission

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With the right tools the government can

•Build new applications not possible before

•Enhance service to citizens significantly

•Remove data redundancy

•Decrease time to mission

•Reduce cost

Big Data Is An OpportunityBig Data Is An Opportunity

Page 5: Webinar: How MongoDB is making Government Better, Faster, Smarter

MongoDB

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MongoDB

The leading NoSQL database

Document Database

Open-Source

General Purpose

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4,000,000+ 4,000,000+ MongoDB DownloadsMongoDB Downloads

100,000+ 100,000+ Online Education RegistrantsOnline Education Registrants

20,000+ 20,000+ MongoDB User Group MembersMongoDB User Group Members

20,000+ 20,000+ MongoDB Days AttendeesMongoDB Days Attendees

15,000+ 15,000+ MongoDB Management Service (MMS) UsersMongoDB Management Service (MMS) Users

Global Community

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Indeed.com Trends

Top Job Trends

1.HTML 5

2.MongoDB

3.iOS

4.Android

5.Mobile Apps

6.Puppet

7.Hadoop

8.jQuery

9.PaaS

10.Social Media

Leading NoSQL Database

LinkedIn Job Skills

MongoDB

Competitor 1

Competitor 2

Competitor 3

Competitor 4

Competitor 5

All Others

Google Search

MongoDB

Competitor 1

Competitor 2

Competitor 3

Competitor 4

Jaspersoft Big Data Index

Direct Real-Time Downloads

MongoDB

Competitor 1

Competitor 2

Competitor 3

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To provide the best database for how we build and run apps today

MongoDB Vision

Build–New, complex, varying data–Flexibility–New languages–Faster development

Run–Big Data scalability–Real-time–Commodity hardware–Cloud

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Agility

How?

Scalability

$Value

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RDBMS

Agility – Document Oriented Model

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" }

] }

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• MongoDB does not need any pre-defined data schema.

• Every document could have different data

Agility – Dynamic Schema Agility – Dynamic Schema

{name: “jeff”, eyes: “blue”, height: 72, boss: “ben”}

{name: “brendan”, aliases: [“el diablo”]}

{name: “ben”, hat: ”yes”}

{name: “matt”, pizza: “DiGiorno”, height: 74, boss: 555.555.1212}

{name: “will”, eyes: “blue”, birthplace: “NY”, aliases: [“bill”, “la ciacco”], gender: ”???”, boss: ”ben”}

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Agility – Rich Query and Aggregation

{

object: ‘M1 Abrahms 3123’,

type: ‘Armored Vehicle’,

owner: ‘5th Armored’,

location: [45.123,47.232],

current_range: 245

armament: [

{ model: ‘105mm M68A1’,

type: ‘Rifled Cannon’,

range: 100000, … },

{ model: ‘120mm M256’,

type: ‘Smooth Bore Cannon’}],

crew: [ {name: ‘Paul’, …

weight: 126000,

equipment: […

desc: “This unit is highly …

}

Rich Queries• Find all armored vehicle under 64 tons

with a smooth bore cannon and a crew member with IED removal training

Geospatial• Find all units within a 220 mile radius of

a position with transport capacity of 20 sorted by proximity

Text Search • Find all units having Arabic mentioned

Aggregation• Calculate the average range of units

within the Afghanistan Theater of Operation

Map Reduce• Find correlations between co-located

units and mission casualties

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• Organization focused on mobile development

• Many apps geospatially enabled

• Agile development, SCRUM

• Originally Native/Java Services/PostGRES

• Moved to Native/Node.JS/MongoDB

Use Case: Mobile Development

• Constant model changes

• JSON throughout

• Development velocity was more than doubled

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• Executive order for agencies to open data

• History of MongoDB as back end for data services

• Data services expose data in JSON/XML

• Existing tools lack flexibility and scalability

• We are seeing powerful and scalable platforms built on top of MongoDB

• Platform doesn’t need to know or care what the data looks like

• http://cfpb.github.io/qu/

Use Case: Open Data Initiative

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Agility – Native Language Drivers

ShellCommand-line shell for interacting directly with database

DriversDrivers for most popular programming languages and frameworks

> db.collection.insert({company:“10gen”, product:“MongoDB”})> > db.collection.findOne(){

“_id”: ObjectId(“5106c1c2fc629bfe52792e86”),“company”: “10gen”“product”: “MongoDB”

}

Java

Python

Perl

Ruby

Haskell

JavaScript

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Better Data Locality

Scale - Performance

In-Memory Caching

In-Place Updates

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Scale – Auto-Sharding

Auto-Sharding

• Increase capacity as you go

• Commodity and cloud architectures

• Improved operational simplicity and cost visibility

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Scale – HA & Replication

• Automated replication and failover

• Multi-data center support

• Improved operational simplicity (e.g., HW swaps)

• Data durability

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Scale - Global Data Distribution

Real-time

Real-time Real-time

Real-time

Real-time

Real-time

Real-time

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Scale - Read Global/Write Local

Primary:NYC

Secondary:NYC

Primary:LON

Primary:SYD

Secondary:LON

Secondary:NYC

Secondary:SYD

Secondary:LON

Secondary:SYD

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• Project in the IC

• Needle in the haystack for changing datasets

Use Case: The Graveyard

• 7 previous technologies

• Speed in ingestion, simple and agile usage

• 500k TPS over 50 nodes

• Breadth of querying and indexing important

• Millions saved in total cost

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Developer/Ops Savings•Ease of Use•Agile development•Less maintenance

Hardware Savings•Commodity servers•Internal storage (no SAN)•Scale out, not up

Software/Support Savings•No upfront license•Cost visibility for usage growth

Value - Lower TCO

DB Alternative

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• MongoDB a great fit for many problems in Healthcare

• Lots of document oriented data already

• Complex, varying, unstructured data

• $10 Billion non-profit health conglomerate

• Insurance companies

• RelayHealth

• Usage within the VA

• popHealth

• Cypress

Use Case: Healthcare

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MongoDB Products and Services

TrainingOnline and In-Person for Developers and Administrators

MongoDB Management Service (MMS)Cloud-Based Suite of Services for Managing MongoDB Deployments

SubscriptionsMongoDB Enterprise, MMS (On-Prem), Professional Support, Commercial License

ConsultingExpert Resources for All Phases of MongoDB Implementations

Page 26: Webinar: How MongoDB is making Government Better, Faster, Smarter