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Sql vs no sql diponkar paul-april 2020-Toronto PASS

Sql vs no sql diponkar paul-april 2020-Toronto PASS

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NoSQL database have grown popularity in recent years due to the flexibility of data modeling and scaling up capabilities. NoSQL database also have been using in big data landscape. The demo rich session will elaborate difference between SQL and NoSQL.

NoSQL database have grown popularity in recent years due to the flexibility of data modeling and scaling up capabilities. NoSQL database also have been using in big data landscape. The demo rich session will elaborate difference between SQL and NoSQL.

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Sql vs no sql diponkar paul-april 2020-Toronto PASS

  1. 1. SQL vs. NoSQL (looking at NoSQL database from the view of a SQL database professional)
  2. 2. Father and Husband Blogger Data Engineer Diverse background Community Twitter: @Paulswengrr Blog: www.allaboutdata.ca
  3. 3. What we cover Refresh our memory with traditional SQL Know about NoSQL (MongoDB) Demo Comparison
  4. 4. SQL Syntax SELECT Id, Product, Price From Product Where ProductCategory=’Bikes’ Join, Insert, Update, Delete
  5. 5. Schema CREATE TABLE [Production].[Product]( [ProductID] [int] IDENTITY(1,1) NOT NULL, [Name] [nvarchar](100) NOT NULL, [ProductNumber] [nvarchar](25) NOT NULL, [MakeFlag] [dbo].[Flag] NOT NULL, [FinishedGoodsFlag] [dbo].[Flag] NOT NULL, [Color] [nvarchar](15) NULL, [SafetyStockLevel] [smallint] NOT NULL, [StandardCost] [money] NOT NULL, [ListPrice] [money] NOT NULL, [Size] [nvarchar](5) NULL)
  6. 6. Relationship/Normalization Customer Bridge table (Order) Product Id Name Price Description 1 “Mountain Bike “ 2500 “Bike for mountain trek” 2 “City Bike” 1000 “Best fit to roam around city” Id Customer_ID Product_ID 1 2 1 2 2 2 3 1 1 Id Name Email 1 Morten Sorenson m.s@outlook.com 2 Andersen Lu al@yahoo.com 3 Derek Paul dp@outlook.com
  7. 7. Type of relationships
  8. 8. NoSQL • MongoDB • Azure Cosmos DB • Amazon Document DB • Oracle NoSQL • Google BigTable
  9. 9. NoSQL- MongoDB “MongoDB” derives from the word “humongous”
  10. 10. Database E-Commerce Collections Table –Customer, Product… Documents {“Name”: ”Anders”, age:36} {“Name”: “Carsten”, age:42}
  11. 11. No Schema Id:1 Age:36Name: ‘Anders’ ….. Id:2 Age:36 Name: ‘Carsten’ ….. Id:3 …..
  12. 12. NoSQL –No relation Profession {id:1,profession:’Developer’} {id:2, profession: ’Data Engineer’} {id:3, profession: ’Actor’} Users {id:1,name:’Tom Hanks’, age:20} {id:2,name:’Casper Ruther’, age:42} {id:3,name:’Paul Anders’, age:63} db.Users.insert( { id:"01", name:"Tom Hanks", age:20 email:"th@hollywood.com", Profession:["Developer","Data Engineer","Actor"] } ) Usersprofession {id:1,userId:1,professionId:1} {id:2,userId:1, professionId: 2} {id:3,userId: 1, professionId: 3} {id:4,userId: 2, professionId: 2}
  13. 13. Tools: MongoDB https://www.mongodb.com/products/compass Robo 3T: https://robomongo.org/ https://docs.mongodb.com/manual/core/data-model-design/ https://docs.mongodb.com/manual/reference/method/db.collection.update/
  14. 14. Languages • MONGO SHELL • Python • java • C# • Scala • GO and many more.
  15. 15. Demo
  16. 16. SQL vs NoSQL SQL NoSQL Data uses Schema Schema-less (Schema Agnostic) Maintain Relationship No relations– though you can design relationship Data distributed in multiple tables Data in one table (embedded) Monolithic, you can easily Scale-Up. Scale out is also possible but difficult (e.g. Azure Elastic Database tools) Scale up and scale out- Globally distributed

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