advanced applications with mongodb
TRANSCRIPT
3
Agenda
Introduction MongoDB
General Aspects of Databases
Modern Age Applications
Available Infrastructure
4
Introduction
Norberto LeiteTechnical Evangelist
Madrid, Spain
http://www.mongodb.com/norberto
@nleite
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THE LARGEST ECOSYSTEM
9,000,000+MongoDB Downloads
250,000+Online Education Registrants
35,000+MongoDB User Group Members
35,000+MongoDB Management Service (MMS) Users
750+Technology and Services Partners
2,000+Customers Across All Industries
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We are Local!http://www.meetup.com/Madrid-MongoDB-User-Group/events/223154279/
• 1047 members and growing• Next event 24/06
MongoDB, Inc.
400+ employees 2,000+ customers
Over $311 million in funding13 offices around the world
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Enabling New Apps Better Customer Experience
Lower TCOFaster Time to Value
MongoDB Business Value
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Expressive Query
Language
StrongConsistency
Secondary Indexes
Flexibility
Scalability
Performance
Relational
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Relational Database Challenges
Data Types
Unstructured data
Semi-structured data
Polymorphic data
Agile Development
Iterative
Short development cycles
New workloads
Volume of Data
Petabytes of data
Trillions of records
Millions of queries/sec
New Architectures
Horizontal scaling
Commodity servers
Cloud computing
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NoSQL
Expressive Query
Language
StrongConsistency
Secondary Indexes
Flexibility
Scalability
Performance
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Expressive Query
Language
StrongConsistency
Secondary Indexes
Flexibility
Scalability
Performance
Relational NoSQL
Relational + NoSQL
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Expressive Query
Language
StrongConsistency
Secondary Indexes
Flexibility
Scalability
Performance
Nexus Architecture
Relational + NoSQL
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The Database of the Post-Relational Era
Combines the foundation of relational databases with the innovations of NoSQL
Flexible Data ModelPerformanceScalability
NoSQLStrong ConsistencyPowerful Query LanguageRich Indexes
RELATIONAL
Factors Driving Modern Applications
Data
• 90% data created in last 2 years
• 80% enterprise data is unstructured
• Unstructured data growing 2X rate
of structured data
Mobile
• 2 Billion smartphones by 2015
• Mobile now >50% internet use
• 26 Billion devices on IoT by
2020
Social
• 72% of internet use is social media
• 2 Billion active users monthly
• 93% of businesses use social media
Cloud
• Compute costs declining 33% YOY
• Storage costs declining 38% YOY
• Network costs declining 27% YOY
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Data Consolidation
Data Warehouse
Real-time orBatch
Engagement Applicaiton
Engagement Applicaiton
Operational Data Hub Benefits• Real-time• Complete details• Agile• Higher customer
retention• Increase wallet share• Proactive exception
handling
Stra
tegi
c Re
porti
ng
Operational Reporting
Cards
Loans
Deposits
Cards Data Source 1
LoansData Source 2
Deposits
…
Data Source n
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Molecular Similarity Database
• Store Chemical Compounds – Fingerprints
• Want to find compounds which are “close” to a given compound
• Need to return quickly a small set of reasonable candidates
• Few researchers working concurrently
• Use Tanimoto association coefficient to compare two compounds based on their common fingerprints
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Big Data Genomics
• Very large base of DNA sample sequences– Origin, collection method,
sequence, date, …• Enumeration of mutations relative
to reference sequence– Positions, mutation type, base
• Need to retrieve efficiently all sequences showing a particular mutation
• Similar to Content Management System pattern
• Add tag array in sequence document with mutation names
• Index tag array• Queries looking for affected
sequences are indexed and very fast
• Easy to setup, flexible representation and details for sequences, flexible evolution
• Can scale to massive volumes
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IoT: Large Industrial Vehicle Manufacturer
Shard 1Secondary
Shard 2Secondary
Shard 3Secondary
Shard 1Primary
Shard 1Secondary
Shard 1Primary
Shard 1Secondary
Shard 1Primary
Shard 1Secondary
Central Hub
RegionalHub
RegionalHub
RegionalHub
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Not Necessarily!
Have you ever needed:- Change the Schema ?- Iterate Faster ?- Different Data Types ?- Geospatial Capabilities?
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MOBILE IS HARD MONGODB MAKES IT EASY
Document Model
Dynamic Schema
Horizontal Scalability
New Data
Streams of Fast Data
Scaling Problems
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CATALOGS ARE HARD MONGODB MAKES IT EASY
Do the Impossible
Faster
Query Language & Aggregation Framework
Stagnant
Heterogeneous Data
Feature Tradeoffs
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CATALOGS ARE HARD MONGODB MAKES IT EASY
Tailor Made To Innovate
Adjust To Your Business Needs
Open Source
Hard to Innovate
Can't Customize at Speed
Expensive
Infrastructure
• “ … the basic equipment and structures (such as roads and bridges) that are needed for a country, region, or organization to function properly …”
http://www.merriam-webster.com/dictionary/infrastructure
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What we discovered today
• Today we have a lot of choices– For building applications– For storing data– For deployment and infrastructure
• Our Apps are ever more– Dynamic– Fast paced – Demanding
• Change is constant and should be embraced• MongoDB is here to help you
– Scale – Iterate– Get more out of your ideas!
Engineering
Sales & Account Management Finance & People Operations
Pre-Sales Engineering Marketing
Join the Team
View all jobs and apply: http://grnh.se/pj10su