+++moderndatabases-180422125041yrhthythy.pptx

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1. Modern Databases And its Challenges

2. Outline The objective of databases The Relational Model and ACID rules The Distributed Systems and CAP Theorem The NoSQL Databases The NewSQL Databases

3. Why need databases Availability : data are made available to wide variety of users Integrity : the data available in the database is a reliable data Security : only authorized users can access the data Independence : users deal with data in efficient manner , “ abstract view ” of how the data is stored in the database.

4. The Relational model The current traditional Databases such as (SQL Server, Oracle, MySQL …. etc.). The Idea of relational model come at 1970 Is very stable architecture The most popular model for storing data in the web and business applications till now has fixed structure for database schema Relational model databases depend on Transactions and it’s ACID rules

5. ACID Rules Atomic : A transaction is a logical unit of work which must be either completed with all of its data modifications, or none of them is performed. Consistent : At the end of the transaction, all data must be left in a consistent state. Isolated : Modifications of data performed by a transaction must be independent of another transaction. Unless this happens, the outcome of a transaction may be erroneous. Durable : When the transaction is completed, effects of the modifications performed by the transaction must be permanent in the system.

6. The problem with Relational Model Some datatypes not suitable for traditional database (Graph , unstructured) Scalability problem : and it’s Cost Agility challenges that face modern applications (Schema Free)

7. Distributed Systems A distributed system consists of multiple computers and software components that communicate through a computer network  A distributed system can consist of any number of possible configurations, such as mainframes, workstations, personal computers, and so on. The computers interact with each other and share the resources of the system to achieve a common goal .

8. CAP Theorem CAP theorem states that there are three basic requirements which exist in a special relation when designing applications for a distributed architecture Consistency  - This means that the data in the database remains consistent after the execution of an operation. For example after an update operation all clients see the same data. Availability  - This means that the system is always on ( Every request receives response ), no downtime. Partition Tolerance  - This means that the system continues to function even the communication among the servers is unreliable (nodes are up, but can't communicate) Ex: if the network stops delivering messages between two sets of servers, will the system continue to work correctly?

9. CAP Theorem In theoretically it is impossible to fulfill all 3 requirements Relational Databases achieve Availability Every request receives a (non-error) response Consistency All clients always have the same view of data No Partition Tolerance

10. What is NoSQL non-relational database management systems It is designed for distributed data stores where very large scale of data storing needs Scale Horizontally Schema Free

11. Why NoSQL The huge contents generated every time by humans, devices, machines… etc. Certain types of data Agility challenges that face modern applications

12. History of NoSQL The term NoSQL was coined by Carlo Strozzi in the year 1998. He used this term to name his database which did not have an SQL interface. In the early 2009, in an event on open-source distributed databases the term reused to refer databases which are non-relational, distributed, and does not conform to ACID. In the same year, the " no:sql (east)" conference held in Atlanta, USA, NoSQL was discussed. And then, discussion and practice of NoSQL got a momentum, and NoSQL saw an unprecedented growth.

13. NoSQL Consistency According to CAP Theorem it is impossible to fulfill all 3 requirements NoSQL Databases achieves No Consistency may some clients have different views of data Availability all nodes are always in contact Partition Tolerance system continues to function even the communication among the servers is unreliable

14. NoSQL Consistency In 2007, Amazon discovered that every 100ms of latency on the Amazon website cost 1% in sales. At the time their annual sales were around $14.7 billion. And 1% of $14.7 billion is a lot of sales to lose. they outlined an approach for a new kind of database. One that guaranteed Availability and Partition tolerance at the expense of Consistency. They rely on Eventual Consistency, where data would be consistent in the end (after some of time). For a bank where transactions have to be consistent, that just wouldn’t work . For companies like Google, it’s acceptable.

15. Types of NoSQL Databases Key-Value Store It has a Big Hash Table of keys & values { Riak , Amazon S3 (Dynamo)} Column-based Store Each storage block contains data from only one column, {HBase, Cassandra} Document-based   Store It   stores documents made up of tagged elements. {CouchDB, MongoDB} Graph-based A network database that uses edges and nodes to represent and store data. {Neo4J}

16. Advantages and Disadvantages Advantages  Disadvantages High scalability No standardization Distributed Computing Limited query capabilities (so far) Lower cost Eventual consistent Schema flexibility, semi-structure data Less support and tools compared to relational databases No complicated Relationships Very Easy software development

17. Example of NoSQL (MongoDB , C#) 1 2 3

18. Example of NoSQL (MongoDB)

19. The NewSQL is a class of modern relational database management systems that seek to provide the same scalable performance of NoSQL systems for online transaction processing (OLTP) read-write workloads while still maintaining the ACID guarantees of a traditional database system. How? Minimize the Locking Avoid Table or Row level locking Heavily depend on Memory

20. NuoDB Architecture Transaction Engines (TEs): The transaction processing layer is made up of in-memory process nodes that coordinate with each other and the storage management layer. Nodes can be easily added or removed to align with transaction volume. Storage Managers (SMs): The storage management layer consists of process nodes that have both in-memory and on-disk storage components. SMs provide on-disk data durability guarantees, and multiple SMs can be used to increase data redundancy. Multi-version concurrency Management Tire

21. How to choose It depends The degree of consistency and integrity The scalability you need The complexity of data model the query complexity Your team knowledge

22. How about hybrid SQL NoSQL Integration Application

23. References https://www.red-gate.com/simple-talk/opinion/opinion-pieces/does-nosql--nodba/?utm_source=simpletalk&utm_medium=weblink&utm_content=sombrero&utm_campaign=magazine https://www.w3resource.com/mongodb/nosql.php https://www.mongodb.com/nosql-explained?jmp=footer https://en.wikipedia.org/wiki/NewSQL https://en.wikipedia.org/wiki/CAP_theorem http://galaldev.blogspot.com.eg/2017/02/sql-server-transaction.html