MongoDB at FrozenRails
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The document describes MongoDB as an open-source, high-performance, document-oriented database. It stores data in flexible, JSON-like documents, with schemaless collections. It supports dynamic queries, indexing, aggregation and scaling horizontally. MongoDB is suited for scaling out web applications, caching, and high volume use cases where SQL may not be a good fit.
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MongoDB at FrozenRails
- 1. open-‐source, high-‐performance, document-‐oriented database Mike Dirolf • 10gen, Inc. • @mdirolf • http://dirolf.com
- 2. Non-relational Operational Stores (“NoSQL”) New Gen. OLAP RDBMS (vertica, aster, greenplum) (Oracle, MySQL)
- 3. NoSQL Really Means: non-‐relational, next-‐generation operational datastores and databases
- 4. no joins + no complex transactions Horizontally Scalable Architectures
- 5. no joins + no complex transactions New Data Models
- 6. New Data Models improved ways to develop applications?
- 7. Data Models Key / Value memcached, Dynamo Tabular BigTable Document Oriented MongoDB, CouchDB
- 8. • memcached scalability & performance • key/value • RDBMS depth of functionality
- 9. JSON-style Documents represented as BSON {“hello”: “world”} x16x00x00x00x02hello x00x06x00x00x00world x00x00 http://bsonspec.org
- 10. Flexible “Schemas” {“author”: “eliot”, {“author”: “mike”, “text”: “...”, “text”: “...”} “tags”: [“mongodb”]}
- 11. Dynamic Queries
- 12. Atomic Update Modifiers
- 14. Replication master slave master master slave slave slave slave master master slave master
- 15. Auto-sharding Shards mongod mongod mongod ... Config mongod mongod mongod Servers mongod mongod mongod mongos mongos ... client
- 16. Many Supported Platforms / Languages
- 17. Best Use Cases T Scaling Out Caching The Web High Volume
- 18. Less Good At highly transactional ad-‐hoc business intelligence problems that require SQL
- 19. A Quick Aside _id special key present in all documents unique across a Collection any type you want
- 20. Post {:author => “mike”, :date => Time.new, :text => “my blog post...”, :tags => [“mongodb”, “ruby”]}
- 21. Comment {:author => “eliot”, :date => Time.new, :text => “great post!”}
- 22. New Post post = {:author => “mike”, :date => Time.new, :text => “my blog post...”, :tags => [“mongodb”, “ruby”]} db[“posts”].save(post)
- 23. Embedding a Comment c = {:author => “eliot”, :date => Time.new, :text => “great post!”} db[“posts”].update({:_id => post[:_id]}, {:$push => {:comments => c}})
- 24. Posts by Author db[“posts”].find(:author => “mike”)
- 25. Last 10 Posts db[“posts”].find .sort([[:date, :desc]]) .limit(10)
- 26. Posts Since April 1 april_1 = Time.utc(2010, 4, 1) db[“posts”].find(:date => {:$gt => april_1})
- 27. Posts Ending With ‘Ruby’ db[“posts”].find(:text => /Ruby$/)
- 28. Posts With a Tag db[“posts”].find(:tags => “mongodb”) ...and Fast (multi-‐key indexes) db[“posts”].create_index(“tags”)
- 29. Indexing / Querying on Embedded Docs (dot notation) db[“posts”].create_index(“comments.author”) db[“posts”].find(“comments.author” => “eliot”)
- 30. Counting Posts db[“posts”].count db[“posts”].find(:author => “mike”).count
- 31. Basic Paging page = 2 page_size = 15 db[“posts”].find.limit(page_size) .skip(page * page_size)
- 32. Migration: Adding Titles (just start adding them) post = {:author => “mike”, :date => Time.new, :text => “another blog post...”, :tags => [“mongodb”], :title => “MongoDB for Fun and Profit”} post_id = db[“posts”].save(post)
- 33. Advanced Queries $gt, $lt, $gte, $lte, $ne, $all, $in, $nin $not, $mod, $size, $exists, $type, $elemMatch db[“posts”].find(:$where => “this.author == ‘mike’ || this.title == ‘foo’”)
- 35. Other Cool Stuff aggregation and map/reduce capped collections unique indexes mongo shell GridFS geo
- 36. Download MongoDB http://www.mongodb.org and let us know what you think @mdirolf @mongodb
Editor's Notes
- Collection (logical groupings of documents) Indexes are per-collection
- blog post twitter