MongoDB @ Johannesburg day 2

Transcript

2. MongoDB Introduction Bill Brooks – Territory Manager, SEMEA Norberto Leite – Senior Solutions Architect, SEMEA
3. 3 MongoDB The leading NoSQL database Document Database Open- Source General Purpose
4. 4 MongoDB Business Value Enabling New Apps Better Customer Experience Lower TCO Faster Time to Market
5. 5 To provide the best database for how we build and run apps today MongoDB Vision Build –  New and complex data –  Flexible –  New languages –  Faster development Run –  Big Data scalability –  Real-time –  Commodity hardware –  Cloud
6. 6 4,000,000+ MongoDB Downloads 100,000+ Online Education Registrants 20,000+ MongoDB User Group Members 20,000+ MongoDB Days Attendees 15,000+ MongoDB Management Service (MMS) Users Global Community
7. 7 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
8. 8 Data Hub User Data Management Big Data Content Mgmt & Delivery Mobile & Social MongoDB Solutions
9. 9 MongoDB Partners (200+) Software & Services Cloud & Channel Hardware
10. 10 Relational Database Challenges Data Types •  Unstructured data •  Semi-structured data •  Polymorphic data Volume of Data •  Petabytes of data •  Trillions of records •  Millions of queries per second Agile Development •  Iterative •  Short development cycles •  New workloads New Architectures •  Horizontal scaling •  Commodity servers •  Cloud computing
11. 11 RDBMS Agility 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" } ] }
12. 12 MongoDB Performance* Top 5 Marketing Firm Government Agency Top 5 Investment Bank Data Key/value 10+ fields, arrays, nested documents 20+ fields, arrays, nested documents Queries Key-based 1 – 100 docs/query 80/20 read/write Compound queries Range queries MapReduce 20/80 read/write Compound queries Range queries 50/50 read/write Servers ~250 ~50 ~40 Ops/sec 1,200,000 500,000 30,000 * These figures are provided as examples. Your application governs your performance.
13. 13 MongoDB Features •  JSON Document Model with Dynamic Schemas •  Auto-Sharding for Horizontal Scalability •  Text Search •  Aggregation Framework and MapReduce •  Full, Flexible Index Support and Rich Queries •  Built-In Replication for High Availability •  Advanced Security •  Large Media Storage with GridFS
14. 14 MongoDB and Enterprise IT Strategy Legacy Strategic Apps On-Premise SaaS, Mobile, Social Database Oracle MongoDB Offline Data Teradata Hadoop Compute Scale-Up Server Commodity HW / Cloud Storage SAN Local Storage / Cloud Network Routers and Switches Software-Defined Networks
15. 15 MongoDB and Enterprise IT Stack EDW Hadoop Management & Monitoring Security & Auditing RDBMS CRM, ERP, Collaboration, Mobile, BI OS & Virtualization, Compute, Storage, Network RDBMS Applications Infrastructure Data Management Online Data Offline Data
16. MongoDB Solution
17. 17 Better Data Locality Performance In-Memory Caching In-Place Updates
18. 18 Scalability Auto-Sharding •  Increase capacity as you go •  Commodity and cloud architectures •  Improved operational simplicity and cost visibility
19. 19 High Availability •  Automated replication and failover •  Multi-data center support •  Improved operational simplicity (e.g., HW swaps) •  Data durability and consistency
20. 20 MongoDB Architecture
21. 21 It Hides What You’re Really Doing
22. 22 Document Model Benefits •  Agility and flexibility –  Data models can evolve easily –  Companies can adapt to changes quickly •  Intuitive, natural data representation –  Developers are more productive –  Many types of applications are a good fit •  Reduces the need for joins, disk seeks –  Programming is more simple –  Performance can be delivered at scale
23. 23 Developers are more productive
24. 24 Developers are more productive
25. 25 Developers are more productive
26. 26 MongoDB is full featured MongoDB Rich Queries •  Find Paul’s cars •  Find everybody in London with a car built between 1970 and 1980 Geospatial •  Find all of the car owners within 5km of Trafalgar Sq. Text Search •  Find all the cars described as having leather seats Aggregation •  Calculate the average value of Paul’s car collection Map Reduce •  What is the ownership pattern of colors by geography over time? (is purple trending up in China?) { ! first_name: ‘Paul’,! surname: ‘Miller’,! city: ‘London’,! location: [45.123,47.232],! cars: [ ! { model: ‘Bentley’,! year: 1973,! value: 100000, … },! { model: ‘Rolls Royce’,! year: 1965,! value: 330000, … }! }! }!
27. 27 Shell Command-line shell for interacting directly with database Shell and Drivers Drivers Drivers for most popular programming languages and frameworks > db.collection.insert({product:“MongoDB”, type:“Document Database”}) > > db.collection.findOne() { “_id” : ObjectId(“5106c1c2fc629bfe52792e86”), “product” : “MongoDB” “type” : “Document Database” } Java Python Perl Ruby Haskell JavaScript
28. Use Cases
29. 29 Serves targeted content to users using MongoDB- powered identity system Case Study Problem Why MongoDB Results •  20M+ unique visitors per month •  Rigid relational schema unable to evolve with changing data types and new features •  Slow development cycles •  Easy-to-manage dynamic data model enables limitless growth, interactive content •  Support for ad hoc queries •  Highly extensible •  Rapid rollout of new features •  Customized, social conversations throughout site •  Tracks user data to increase engagement, revenue
30. 30 Insurance leader generates coveted 360-degree view of customers in 90 days – “The Wall” Case Study Problem Why MongoDB Results •  No single view of customer •  145 yrs of policy data, 70+ systems, 15+ apps •  2 years, $25M trying to aggregate in RDBMS – failed •  Agility – prototype in 5 days; production in 90 days •  Dynamic schema & rich querying – combine disparate data into one data store •  Hot tech to attract top talent •  Increased call center productivity •  Better customer experience, reduced churn, more upsell opps •  Dozens more projects in the works to leverage this data platform
31. 31 Stores one of world’s largest record repositories and searchable catalogues in MongoDB Case Study Problem Why MongoDB Results •  One of world’s largest record repositories •  Move to SOA required new approach to data store •  RDBMS could not support centralized data mgt and federation of information services •  Fast, easy scalability •  Full query language •  Complex metadata storage •  Will scale to 100s of TB by 2013, PB by 2020 •  Searchable catalogue of varied data types •  Decreased SW and support costs
32. 32 Stores billions of posts in myriad formats with MongoDB Case Study Problem Why MongoDB Results •  1.5M posts per day, different structures •  Inflexible MySQL, lengthy delays for making changes •  Data piling up in production database •  Poor performance •  Flexible document- based model •  Horizontal scalability built in •  Easy to use •  Interface in familiar language •  Initial deployment held over 5B documents and 10TB of data •  Automated failover provides high availability •  Schema changes are quick and easy
33. 33 Uses MongoDB to power enterprise social networking platform Case Study Problem Why MongoDB Results •  Complex SQL queries, highly normalized schema not aligned with new data types •  Poor performance •  Lack of horizontal scalability •  Dynamic schemas using JSON •  Ability to handle complex data while maintaining high performance •  Social network analytics with lightweight MapReduce •  Flexibility to roll out new social features quickly •  Sped up reads from 30 seconds to tens of milliseconds •  Dramatically increased write performance