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OPENEXPO Madrid 2015 - Advanced Applications with MongoDB
The document presents advanced applications of MongoDB, emphasizing its capabilities as a general-purpose document database suitable for modern applications. It discusses the challenges faced by relational databases and highlights MongoDB's features such as scalability, flexibility, and expressive query language. The presentation underscores the evolution in data management and infrastructure required to support dynamic and fast-paced application development.
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OPENEXPO Madrid 2015 - Advanced Applications with MongoDB
- 2. Advanced Applications w/MongoDB Things you perhaps were not aware that MongoDB can do for you!
- 3. 3 Agenda Introduction MongoDB General Aspectsof Databases Modern Age Applications Available Infrastructure
- 4. 4 Introduction Norberto Leite Technical Evangelist Madrid,Spain http://www.mongodb.com/norberto @nleite norberto@mongodb.com
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- 6. 6 MongoDB GENERAL PURPOSE DOCUMENTDATABASE OPEN-SOURCE
- 7. MongoDB is FullyFeatured
- 8. 8 THE LARGEST ECOSYSTEM 10,000,000+ MongoDBDownloads 250,000+ Online Education Registrants 35,000+ MongoDB User Group Members 35,000+ MongoDB Management Service (MMS) Users 900+ Technology and Services Partners 2,000+ Customers Across All Industries
- 9. 9 We are Local! http://www.meetup.com/Madrid-MongoDB-User-Group/events/223154279/ • 1047 members and growing • Next event 24/06
- 10. MongoDB, Inc. 400+ employees2,000+ customers Over $311 million in funding13 offices around the world
- 11. 11 Enabling New AppsBetter Customer Experience Lower TCOFaster Time to Value MongoDB Business Value
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- 13. 13 CREATE APPLICATIONS NEVER BEFOREPOSSIBLE AGILE SCALABLE
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- 16. 16 Relational Database Challenges DataTypes 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
- 17. Does that meanthey are not good anymore?
- 18. 18 No, of coursenot. You are fine!
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- 23. 23 The Database ofthe Post-Relational Era Combines the foundation of relational databases with the innovations of NoSQL Flexible Data Model Performance Scalability NoSQL Strong Consistency Powerful Query Language Rich Indexes RELATIONAL
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- 25. Factors Driving ModernApplications 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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- 27. 27 Data Consolidation Data Warehouse Real-‐/me or Batch Engagement Applicaiton Engagement Applicaiton Opera&onal Data Hub Benefits • Real-‐/me • Complete details • Agile • Higher customer reten/on • Increase wallet share • Proac/ve excep/on handling Strategic Repor/ng Opera/onal Repor/ng Cards Loans Deposits Cards Data Source 1 Loans Data Source 2 Deposits … Data Source n
- 28. 28 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
- 29. 29 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
- 30. 30 IoT: Large IndustrialVehicle Manufacturer Shard 1 Secondary Shard 2 Secondary Shard 3 Secondary Shard 1 Primary Shard 1 Secondary Shard 1 Primary Shard 1 Secondary Shard 1 Primary Shard 1 Secondary Central Hub Regional Hub Regional Hub Regional Hub
- 31. So… just forfancy applications!??!
- 32. 32 Not Necessarily! Have youever needed: - Change the Schema ? - Iterate Faster ? - Different Data Types ? - Geospatial Capabilities?
- 33. 33 MOBILE IS HARDMONGODB MAKES IT EASY Document Model Dynamic Schema Horizontal Scalability New Data Streams of Fast Data Scaling Problems
- 34. 34 CATALOGS ARE HARDMONGODB MAKES IT EASY Do the Impossible Faster Query Language & Aggregation Framework Stagnant Heterogeneous Data Feature Tradeoffs
- 35. 35 CATALOGS ARE HARDMONGODB MAKES IT EASY Tailor Made To Innovate Adjust To Your Business Needs Open Source Hard to Innovate Can't Customize at Speed Expensive
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- 38. Infrastructure “ … thebasic 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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- 46. 46 What we discoveredtoday • 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!
- 47. Come and LearnMore https://www.mongodb.com/collateral/mongodb-30-whats-new
- 48. Engineering Sales & AccountManagement Finance & People Operations Pre-Sales Engineering Marketing Join the Team View all jobs and apply: http://grnh.se/pj10su
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