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1
Open source, high performance database
Presentation by:
Hashim Shaikh
Email: hashim@codeformers.com
2
• Introduction to 10gen
• Comparison between Mumps & MongoDB
• MongoDB built for Electronic Records
• Introduction to MongoDB
• MongoDB Security
• OSEHRA / 10gen Collaboration Effort
3
10gen is the company behind MongoDB.
Set the direction &
contribute code to
MongoDB
Foster community &
ecosystem
Provide MongoDB
management services
Provide commercial
services
Founded in 2007
• Dwight Merriman, Eliot Horowitz
• Doubleclick, Oracle, Marklogic, HP
$73M+ in Funding
• Flybridge, Sequoia, NEA, Union Square
Worldwide Expanding Team
• 140+ employees
• NY, Palo Alto, London, Dublin, Sydney
4
Community
• 9,000 people participated in 23 MongoDB Days in 2011
• 42 MongoDB User Groups
• Global reach with events in London, Munich, Paris, Tokyo, and Beijing
Ecosystem
• IaaS and PaaS partners offer Cloud hosting solutions
• MongoDB Database-as-a-Service offerings available
• Business Intelligence, Security, and Hadoop integration solutions
offered by partners
• Customized hardware and storage
The MongoDB community and ecosystem are
expanding.
Set the direction &
contribute code to
MongoDB
Foster community
& ecosystem
Provide MongoDB
management services
Provide commercial
services
5
TRAINING
for developers and administrators
CONSULTING
expertise on a project basis
SUBSCRIPTIONS
developer and production support, commercial
license and MongoDB Subscriber Edition
10gen provides commercial services for
MongoDB.
Foster community
& ecosystem
Provide
commercial
services
Set the direction &
contribute code to
MongoDB
Foster community &
ecosystem
Provide MongoDB
management services
“MediaMath is growing fast and our data volume throughput requirements are
going up very quickly. MongoDB and 10gen have been extremely helpful
partners for us in scaling our data infrastructure.”
Vince Li
6
Demand for MongoDB,
the document-oriented
NoSQL database, saw
the biggest spike with
over 200% growth in
2011.
#2 ON INDEED’S FASTEST GROWING JOBS JASPERSOFT BIGDATA INDEX
451 GROUP
“MONGODB INCREASING ITS DOMINANCE”GOOGLE SEARCHES
7
• MUMPS
• Created 1960
• Document / Object oriented
database
• Predates C and has a very different
syntax and terminology
• Difficult to hire people that know this
technology
• Expensive to maintain
• Time consuming to change / adapt to new
requirements
• Difficult to integrate with new solutions /
technologies
• MongoDB
• Created 2009
• Document Oriented Database
• Designed with latest NoSQL theory
• Open Source Technology
• Massive Community
• Drives innovation
• Cost effective
• Hot technology, lots of buzz, attracts
sharpest and brightest minds, large user
base
• Easy to find resources with MongoDB skill
sets
• Build from ground up for Cloud
Computing Architecture
8
• Examples: HL7, EDI, MARC, MODS, DDMS
• Electronic records typically document oriented in
nature: XML, JSON, Free text, or even binary
• Massive variation in used fields
– Sparse data problem in RBMS
• Constantly evolving to support all the business cases
• Volume and velocity often in Big Data scale
9
{"ClinicalDocument": {
"recordTarget": {
"patientRole": {
"patient": {
"name": {
"given": "Henry",
"family": "Levin",
"suffix": "the 7th” },
"birthTime": {"value": 19320924} },
"providerOrganization": {"name": "Good Health Clinic"} }
},
"author": {
"time": 20000407130000+0500,
"assignedAuthor": {
"assignedPerson": {"name": {
"given": "Robert",
"family": "Dolin",
"prefix": "Dr.” } },
"representedOrganization": { "name": "Good Health Clinic” } }
}
}
10
MongoDB was
created to make
it easy to code,
scale, and
manage
databases.
Agile and Scalable
11
• Scale horizontally over commodity hardware
• RDBMSs great so keep what works
– Ad hoc queries
– Fully featured indexes
– Secondary indexes
• What doesn’t distribute well?
– Long running multi-row transactions
– Joins
– Both artifacts of the relational data model
• Do not homogenize programming interfaces
• Local storage first class citizen for DB storage
12
General
Purpose
Easy to
Use
Fast &
Scalable
Sophisticated
query language
Full featured
indexes
Rich data
model
Simple to setup
and manage
Native language
drivers in all
popular
languages
Easy mapping
to object
oriented code
Dynamically add
/ remove capacity
with no downtime
Auto-sharding
built in
Operates at in-
memory speed
wherever
possible
13
{
title: ‘MongoDB’,
contributors: [
{ name: ‘Hashim Shaikh’,
email: ‘hashim@10gen.com’ },
{ name: ‘Hayden Gill’,
email: ‘hayden@10gen.com’ }
],
model: {
relational: false,
awesome: true
}
}
14
START TRANSACTION;
INSERT INTO contacts VALUES
(NULL, ‘joeblow’);
INSERT INTO contact_emails VALUES
( NULL, ”joe@blow.com”,
LAST_INSERT_ID() ),
( NULL, “joseph@blow.com”,
LAST_INSERT_ID() );
COMMIT;
MongoDB
db.contacts.save( {
userName: “joeblow”,
emailAddresses: [
“joe@blow.com”,
“joseph@blow.com” ] } );
MySQL
15
16
• MongoDB does not need any pre-defined data schema
• Every document could have different data!
name: “jeff”,
eyes: “blue”,
loc: [40.7, 73.4],
boss: “ben”}
{name: “brendan”,
aliases: [“el diablo”]}
name: “ben”,
hat: ”yes”}
{name: “matt”,
pizza: “DiGiorno”,
height: 72,
loc: [44.6, 71.3]}
{name: “will”,
eyes: “blue”,
birthplace: “NY”,
aliases: [“bill”, “la
ciacco”],
loc: [32.7, 63.4],
boss: ”ben”}
17
Better data locality
Relational MongoDB
In-Memory
Caching
Distributed Architecture
Horizontal Scaling
We just can't get any faster than the way MongoDB handles our data.
Tony Tam
CTO, Wordnik
Replication/HA
18
• SSL
– between client and server
– Intra-cluster communication
• Authorization at the database level
– Read Only/Read+Write/Administrator
• Security Roadmap (tentative)
– Pluggable authentication (PAM) 2.4
– Auditing 2.4
– Cell level security 2.6
– Common Criteria certification
19
NoSQL is
popular for
development &
deployment of
data-centric
applications.
MongoDB makes
it easy to code,
scale, and
operate NoSQL.
10gen is the
company behind
MongoDB
20
Clear Your Doubts

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Mongodb Presentation

  • 1. 1 Open source, high performance database Presentation by: Hashim Shaikh Email: hashim@codeformers.com
  • 2. 2 • Introduction to 10gen • Comparison between Mumps & MongoDB • MongoDB built for Electronic Records • Introduction to MongoDB • MongoDB Security • OSEHRA / 10gen Collaboration Effort
  • 3. 3 10gen is the company behind MongoDB. Set the direction & contribute code to MongoDB Foster community & ecosystem Provide MongoDB management services Provide commercial services Founded in 2007 • Dwight Merriman, Eliot Horowitz • Doubleclick, Oracle, Marklogic, HP $73M+ in Funding • Flybridge, Sequoia, NEA, Union Square Worldwide Expanding Team • 140+ employees • NY, Palo Alto, London, Dublin, Sydney
  • 4. 4 Community • 9,000 people participated in 23 MongoDB Days in 2011 • 42 MongoDB User Groups • Global reach with events in London, Munich, Paris, Tokyo, and Beijing Ecosystem • IaaS and PaaS partners offer Cloud hosting solutions • MongoDB Database-as-a-Service offerings available • Business Intelligence, Security, and Hadoop integration solutions offered by partners • Customized hardware and storage The MongoDB community and ecosystem are expanding. Set the direction & contribute code to MongoDB Foster community & ecosystem Provide MongoDB management services Provide commercial services
  • 5. 5 TRAINING for developers and administrators CONSULTING expertise on a project basis SUBSCRIPTIONS developer and production support, commercial license and MongoDB Subscriber Edition 10gen provides commercial services for MongoDB. Foster community & ecosystem Provide commercial services Set the direction & contribute code to MongoDB Foster community & ecosystem Provide MongoDB management services “MediaMath is growing fast and our data volume throughput requirements are going up very quickly. MongoDB and 10gen have been extremely helpful partners for us in scaling our data infrastructure.” Vince Li
  • 6. 6 Demand for MongoDB, the document-oriented NoSQL database, saw the biggest spike with over 200% growth in 2011. #2 ON INDEED’S FASTEST GROWING JOBS JASPERSOFT BIGDATA INDEX 451 GROUP “MONGODB INCREASING ITS DOMINANCE”GOOGLE SEARCHES
  • 7. 7 • MUMPS • Created 1960 • Document / Object oriented database • Predates C and has a very different syntax and terminology • Difficult to hire people that know this technology • Expensive to maintain • Time consuming to change / adapt to new requirements • Difficult to integrate with new solutions / technologies • MongoDB • Created 2009 • Document Oriented Database • Designed with latest NoSQL theory • Open Source Technology • Massive Community • Drives innovation • Cost effective • Hot technology, lots of buzz, attracts sharpest and brightest minds, large user base • Easy to find resources with MongoDB skill sets • Build from ground up for Cloud Computing Architecture
  • 8. 8 • Examples: HL7, EDI, MARC, MODS, DDMS • Electronic records typically document oriented in nature: XML, JSON, Free text, or even binary • Massive variation in used fields – Sparse data problem in RBMS • Constantly evolving to support all the business cases • Volume and velocity often in Big Data scale
  • 9. 9 {"ClinicalDocument": { "recordTarget": { "patientRole": { "patient": { "name": { "given": "Henry", "family": "Levin", "suffix": "the 7th” }, "birthTime": {"value": 19320924} }, "providerOrganization": {"name": "Good Health Clinic"} } }, "author": { "time": 20000407130000+0500, "assignedAuthor": { "assignedPerson": {"name": { "given": "Robert", "family": "Dolin", "prefix": "Dr.” } }, "representedOrganization": { "name": "Good Health Clinic” } } } }
  • 10. 10 MongoDB was created to make it easy to code, scale, and manage databases. Agile and Scalable
  • 11. 11 • Scale horizontally over commodity hardware • RDBMSs great so keep what works – Ad hoc queries – Fully featured indexes – Secondary indexes • What doesn’t distribute well? – Long running multi-row transactions – Joins – Both artifacts of the relational data model • Do not homogenize programming interfaces • Local storage first class citizen for DB storage
  • 12. 12 General Purpose Easy to Use Fast & Scalable Sophisticated query language Full featured indexes Rich data model Simple to setup and manage Native language drivers in all popular languages Easy mapping to object oriented code Dynamically add / remove capacity with no downtime Auto-sharding built in Operates at in- memory speed wherever possible
  • 13. 13 { title: ‘MongoDB’, contributors: [ { name: ‘Hashim Shaikh’, email: ‘hashim@10gen.com’ }, { name: ‘Hayden Gill’, email: ‘hayden@10gen.com’ } ], model: { relational: false, awesome: true } }
  • 14. 14 START TRANSACTION; INSERT INTO contacts VALUES (NULL, ‘joeblow’); INSERT INTO contact_emails VALUES ( NULL, ”joe@blow.com”, LAST_INSERT_ID() ), ( NULL, “joseph@blow.com”, LAST_INSERT_ID() ); COMMIT; MongoDB db.contacts.save( { userName: “joeblow”, emailAddresses: [ “joe@blow.com”, “joseph@blow.com” ] } ); MySQL
  • 15. 15
  • 16. 16 • MongoDB does not need any pre-defined data schema • Every document could have different data! name: “jeff”, eyes: “blue”, loc: [40.7, 73.4], boss: “ben”} {name: “brendan”, aliases: [“el diablo”]} name: “ben”, hat: ”yes”} {name: “matt”, pizza: “DiGiorno”, height: 72, loc: [44.6, 71.3]} {name: “will”, eyes: “blue”, birthplace: “NY”, aliases: [“bill”, “la ciacco”], loc: [32.7, 63.4], boss: ”ben”}
  • 17. 17 Better data locality Relational MongoDB In-Memory Caching Distributed Architecture Horizontal Scaling We just can't get any faster than the way MongoDB handles our data. Tony Tam CTO, Wordnik Replication/HA
  • 18. 18 • SSL – between client and server – Intra-cluster communication • Authorization at the database level – Read Only/Read+Write/Administrator • Security Roadmap (tentative) – Pluggable authentication (PAM) 2.4 – Auditing 2.4 – Cell level security 2.6 – Common Criteria certification
  • 19. 19 NoSQL is popular for development & deployment of data-centric applications. MongoDB makes it easy to code, scale, and operate NoSQL. 10gen is the company behind MongoDB

Editor's Notes

  • #10: Notice the nested structure here. A bit easier to read with the human eye. Same format used for storage and wire transportation (binary makes it smaller, faster. Good for data transport and requires no special assembly or disassembly on either end – a natural fit for many programming languages!
  • #17: Applications enforce the data “schema” and integrity, much like MUMPS does in VistA