WTF: Document DBs

Transcript

1. Document DBs One of the NoSQL ways to handle your data
2. Document DBs - Definition Document-oriented databases store documents. A document is like a hash, with a unique ID field and values that may be any of a variety of types, including more hashes. Documents can contain nested structures, and so they exhibit a high degree of flexibility, allowing for variable domains. The system imposes few restrictions on incoming data, as long as it meets the basic requirement of being expressible as a document.
3. Document DBs - Major implementations 1. Mongo DB 2. Couch DB
4. Mongo DB - Core design goals Document Database designed with three main goals: scalability, performance and easy data access
5. Mongo DB - Structure
6. Mongo DB - Structure
7. Mongo DB - Create
8. Mongo DB - Read
9. Mongo DB - Read
10. Mongo DB - Read
11. Mongo DB - Read
12. Mongo DB - Read
13. Mongo DB - Read
14. Mongo DB - Update
15. Mongo DB - Update
16. Mongo DB - Delete
17. Mongo DB - Rails Mapping 1. MongoMapper 2. Mongoid
18. Mongo DB - Pro's • Very flexible data model (No schema and nested values) • Handle huge amount of data and requests via horizontal and vertical scaling • Easy to use (Mongo commands close to SQL ones)
19. Mongo DB - Con's • Encourage denormalization of schemas • Mongo flexibility (about field names, ...) could be dangerous • Require some effort to design and manage the data cluster
20. Mongo DB - Additional Features • Replication • Sharding • GeoSpatial Requests • GridFS
21. Mongo DB - Supporting Companies • Foursquare • Bit.ly • CERN (for the LHC) • Heroku • The NY Times
22. References Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement by Eric Redmond and Jim R. Wilson
23. http://platypus.belighted.com/ @stephamant