Best Practices for Migrating RDBMS to MongoDB
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Relational databases are being pushed beyond their limits because of the way we build and run applications today, coupled with growth in data sources and user loads. To address these challenges, many companies, such as MTV and Cisco, have migrated successfully from relational databases to MongoDB. Even if you are not yet at capacity limits, you should learn about a modern database that has a built-in automated failover process, automatic sharding, and native tools that help you to explore your data and understand its structure. In this webinar, we walk through step by step how to migrate from a relational database to MongoDB. We start off by covering schema design and performance aspects and then dive into operational aspects, such as performing seamless migrations without downtime. Topics covered include: Schema Design Data Migration Operational Agility at Scale
Best Practices for Migrating RDBMS to MongoDB
- 1. Best Practices for Migrating From RDBMS to MongoDB Sheeri Cabral, Product Manager, Distributed Systems
- 2. Safe Harbor Statement This presentation contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. Such forward-looking statements are subject to a number of risks, uncertainties, assumptions and other factors that could cause actual results and the timing of certain events to differ materially from future results expressed or implied by the forward-looking statements. Factors that could cause or contribute to such differences include, but are not limited to, those identified our filings with the Securities and Exchange Commission. You should not rely upon forward-looking statements as predictions of future events. Furthermore, such forward-looking statements speak only as of the date of this presentation. In particular, the development, release, and timing of any features or functionality described for MongoDB products remains at MongoDBs sole discretion. This information is merely intended to outline our general product direction and it should not be relied on in making a purchasing decision nor is this a commitment, promise or legal obligation to deliver any material, code, or functionality. Except as required by law, we undertake no obligation to update any forward-looking statements to reflect events or circumstances after the date of such statements.
- 3. Agenda Normalization and MongoDB Schema Design and Performance Seamless no-downtime Migration Q&A 60 minutes
- 4. Who am I?
- 5. Who am I? Masters in Computer Science
- 6. Who am I? Sysadmin for 4 years Masters in Computer Science
- 7. Who am I? Sysadmin for 4 years MySQL DBA for 14 years Masters in Computer Science
- 8. RDBMS = Relational Database Management System
- 11. row ~ document
- 12. table ~ collection row ~ document
- 18. What problems does normalization solve?
- 19. What problems does normalization solve? Hard to update a multi-value data cell
- 21. What problems does normalization solve? Duplicate data leads to data integrity problems when doing updates Hard to update a multi-value data cell
- 22. What problems does normalization solve? Duplicate data leads to data integrity problems when doing updates Hard to update a multi-value data cell Duplicate data wastes resources
- 25. What problems does normalization cause?
- 26. What problems does normalization cause? Transactions (ACID compliance) more difficult
- 27. What problems does normalization cause? Joins are expensive Transactions (ACID compliance) more difficult
- 28. What problems does normalization cause? Joins are expensive Transactions (ACID compliance) more difficult Migrations are not convenient
- 30. Data that is accessed together should be stored together
- 31. users articles
- 32. articles users
- 33. users articles
- 34. // Get the user object > user = db.user.findOne({username: sheeri}); articles users
- 35. // Get the user object > user = db.user.findOne({username: sheeri}); // Get all the articles linked to the person > myArticles = db.articles.find({_id: { $in : people.articles.map(authorId => user._id) } } ) articles users
- 36. // Get the user object > user = db.user.findOne({username: sheeri}); articles users
- 37. // Get the user object > user = db.user.findOne({username: sheeri}); // Get all the articles linked to the person > myArticles = db.articles.find({_id: { $in : people.articles.map(authorId => user._id) } } ) articles users
- 38. Model the objects that your application uses
- 39. users articles
- 40. articles
- 41. users articles
- 43. users
- 44. articles users
- 45. MongoDB
- 47. Data that is accessed together should be stored together
- 49. Relational MongoDB Thinking in Documents https://www.mongodb.com/blog/post/thinking-documents-part-1 6 Rules of Thumb for MongoDB Schema Design https://www.mongodb.com/blog/post/6-rules-of-thumb-for-mongodb- schema-design-part-1
- 50. Relational MongoDB What about indexes?
- 51. Relational MongoDB What about indexes? index index index index index
- 52. Relational MongoDB What about indexes?
- 54. simple = single field What about indexes?
- 55. simple = single field What about indexes? compound = multiple fields
- 56. multi-key = index for arrays and nested arrays simple = single field What about indexes? compound = multiple fields
- 57. multi-key = index for arrays and nested arrays simple = single field Unique or non-unique What about indexes? compound = multiple fields
- 59. What about structure? schema validation
- 60. What about structure? schema validation require fields
- 61. What about structure? schema validation require fields specify data types including enumerated lists
- 62. What about foreign keys?
- 63. What about foreign keys? Do you reallyneed them?
- 64. What about foreign keys? Do you reallyneed them? App validatesfrom db lookups
- 65. What about foreign keys? Do you reallyneed them? App validatesfrom db lookups Why validate again?
- 66. What about foreign keys? Do you reallyneed them? App validatesfrom db lookups Why validate again? How does your app handle failures?
- 67. What about foreign keys?
- 68. What about foreign keys? embed for parent/child
- 69. What about foreign keys? embed for parent/child schema validation and enum for specific values
- 70. What about foreign keys? embed for parent/child schema validation and enum for specific values reference
- 72. What about transactions? Atomicity succeeds or fails completely
- 73. What about transactions? Atomicity succeeds or fails completely Consistency db from one valid state to another
- 74. What about transactions? Atomicity succeeds or fails completely Consistency db from one valid state to another Isolation how/when changes are seen by ops
- 75. What about transactions? Atomicity succeeds or fails completely Consistency db from one valid state to another Isolation how/when changes are seen by ops Durability completion is forever
- 76. What about transactions? MongoDB has transactions across documents, collections, shards, etc.
- 77. Relational MongoDB What about transactions?
- 78. Lots of transactions? Rethink your schema
- 80. articles
- 81. Data that is accessed together should be stored together
- 82. Data that is accessed together should be stored together No downtime seamless migrations
- 83. Change strings to dates
- 84. Code application to handle strings and dates Change strings to dates
- 85. Code application to handle strings and dates Change strings to dates New data stored as dates
- 86. Code application to handle strings and dates update documents one at a time Change strings to dates New data stored as dates
- 87. articles
- 88. 16Mb document size limit
- 89. 16Mb document size limit Hot documents Activity hot spots
- 90. 16Mb document size limit Hot documents Activity hot spots Embed = fast access
- 91. 16Mb document size limit Hot documents Activity hot spots Embed = fast access Large docs use more memory
- 92. articles
- 93. articles
- 95. articles
- 96. articles
- 99. articles
- 103. Building a MongoDB schema Embed if you can 1:few
- 104. Building a MongoDB schema Array of references for separate data 1:many Embed if you can 1:few
- 105. Building a MongoDB schema Array of references for separate data 1:many Embed if you can 1:few Reference for unbounded arrays 1:zillion
- 107. Schema Patterns Polymorphic flexible schema extended reference not just _id
- 108. Schema Patterns Polymorphic flexible schema subset part of data is duplicated by embedding extended reference not just _id
- 109. Schema Patterns Polymorphic flexible schema subset part of data is duplicated by embedding outlier a few documents will overflow extended reference not just _id
- 110. Schema Patterns Polymorphic flexible schema subset part of data is duplicated by embedding outlier a few documents will overflow Building with Patterns blog series: https://www.mongodb.com/blog/post/building-with-patterns-a-summary extended reference not just _id
- 111. From RDBMSto MongoDB Documents do not need to have identical fields
- 112. From RDBMSto MongoDB Documents do not need to have identical fields Data that is accessed together should be stored together
- 113. From RDBMSto MongoDB Documents do not need to have identical fields Data that is accessed together should be stored together Rethink if you have lots of references or transactions
- 114. Credit, Thanks and Links Asya Kamsky Evin Roesle Nick Larew Aly Cabral Wikipedia Thinking in Documents https://www.mongodb.com/blog/post/thinking-documents-part-1 6 Rules of Thumb for MongoDB Schema Design https://www.mongodb.com/blog/post/6-rules-of-thumb-for-mongodb- schema-design-part-1 Building with Patterns blog series: https://www.mongodb.com/blog/post/building-with-patterns-a-summary
- 115. Q&A