When it comes time to select a datastore for your project, there are a bewildering number of choices. How do you know if your project is a good fit for a relational database, or whether one of the many NoSQL options is a better choice? In this webinar you will learn how to evaluate if MongoDB is a fit for your project. You will see how MongoDB's flexible document model is solving business problems in ways that were not previously possible, and how MongoDB's built-in features allow running at extreme scale. Topics will include evaluating MongoDB's functionality, performance, and scalability, as well as a discussion on how to ensure your organization is prepared to run MongoDB in a production environment. Practical examples and customer stories will be included to help you bootstrap your MongoDB evaluation.

1. Best Practices for
Evaluating MongoDB
Thomas Boyd
Senior Solutions Architect, MongoDB
April 2, 2014

2. 2
• Data stores, NoSQL, & MongoDB
• Software Evaluation Principles
• Functionality
• Performance
• Scalability
• Organizational Readiness
• MongoDB “Path to Proof” Program
Agenda

3. Data Stores, NoSQL & MongoDB

4. 4
Data store landscape is Fuzzy
Source: 451 Group, http://blogs.the451group.com/information_management/2012/11/02/updated-database-landscape-graphic, 2012

5. 5
Data store landscape

6. 6
Database for how we build and run many of today’s
applications
MongoDB in Practice
Build
– New and complex data
– Flexible
– New languages
– Faster development
Run
– Big Data scalability
– Real-time
– Commodity hardware
– Cloud
Documents + Rich Data Access +
Performance & Scale

7. Software Evaluation Principles

8. 8
1) Know your Use Case(s)
Three Practical Rules
2) Involve your Stakeholders
3) Formalize you Evaluation

9. 9
Formal Details

10. 10
Formal Summary

11. 11
A Fourth Rule?
4) Fish or Cut Bait

12. Functionality

13. 13
Data Write Functionality
• Data types
• Field-level updates
• Upsert
• Test and Set
• Array operations
• BLOB support
• Transaction support
• more …

14. 14
Data Read Functionality
• Primary key lookups
• Secondary index lookups
• Range scans
• Complex queries
• Aggregations
• Map-Reduce
• Geospatial queries
• Text search
• more…

15. 15
3rd Party Integrations
• ETL Tools
• Reporting Tools
• Hadoop Integrations
• more…

16. 16
Ops/Admin Functionality
• Setup and Maintenance
• Monitoring and troubleshooting
• Security
• High availability
• Geographically distributed clusters
• Backup and Restore
• Chef/Puppet build scripts
• GUI for cluster maintenance
• more…

17. 17
Right Tool for the Right Job

18. 18
Data HubUser Data Management
Big Data Content Mgmt & Delivery Mobile & Social
Wide ranging use cases

19. Performance

20. 20
Understand your Targets
• Crisp definition of each use case/transaction
– Average throughput
– Peak throughput (per second)
– Timing of Peak
– Latency Requirement (95th/99th percentile?)
– Expected change (growth/decline) over time
• Test your Workload
– Full read/write mix
– Maybe multiple scenarios

21. 21
Finding the Knee
working set size
latency
throughput
i/o boundmemory

22. 22
Isolate & Measure
• Clean, repeatable tests
• Automate metrics gathering
• Look for bottlenecks at all components/layers
– CPU
– Disk
– Network
– Application/test harness tier
– Data store tier

23. 23
Selecting a Test Harness
• Time invested versus meaningful results
– Your full application stack
– Running your app code inside test harness
– Generic DB test harnesses
• Understand critical MongoDB settings
– Write concern, read preference, connection pool
size, etc.

24. 24
MongoDB: Schema & Indexing
• Look out for a few common mistakes
– Breaking data into to many separate documents
– Documents that grow without bounds
– Missing or sub-optimal indexes
– Too many indexes
– Expecting change (growth/decline) over time
• Lots of experience with different use cases:
http://docs.mongodb.org/ecosystem/use-cases/

25. Scalability

26. 26
Looking for linear scaling
Number of nodes
latency
throughput

27. 27
MongoDB: Replica Set & Sharing
• Replica Sets
– High availability
– Maintenance
– Workload isolation
– Some read scaling
• Sharding
– Horizontal scaling
– Shard key is crucial
– # of router processes

28. 28
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.

29. 29
A word about Gorillas

30. Organizational Readiness

31. 31
Lots of Resources
Resource Location
MongoDB Downloads mongodb.com/download
Free Online Training education.mongodb.com
Webinars and Events mongodb.com/events
White Papers mongodb.com/white-papers
Case Studies mongodb.com/customers
Presentations mongodb.com/presentations
Documentation docs.mongodb.org
Additional Info info@mongodb.com
Resource Location

32. 32
MongoDB Products and Services
Training
Online and In-Person for Developers and Administrators
MongoDB Management Service (MMS)
Cloud-Based Suite of Services for Managing MongoDB
Deployments
Subscriptions
MongoDB Enterprise, MMS (On-Prem), Professional
Support, Commercial License
Consulting
Expert Resources for All Phases of MongoDB Implementations

33. 33
Manage you Project’s Risk
• Understand Project Criticality
• Training
• Proactive monitoring
• Development to Operations Handoff Procedures
• Defined escalation paths
• Testing, including Ops Procedures

34. MongoDB Path to Proof Program

35. 35
Path to Proof Program
• MongoDB Engineering sponsored Program
– Personal, expert advice on your project
– Accelerate your evaluation of MongoDB
– Complementary – No Obligation
– Limited Time Offer

36. 36
Path to Proof Program
• Three Simple Steps
– Form: http://www.mongodb.com/lp/path-proof-program
– MongoDB Engineer will evaluate fit for Program
– If accepted, account rep with coordinate call with
MongoDB Engineer

37. http://www.mongodb.com/lp/path-proof-program