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A Seminar on NoSQL Databases.

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A Seminar on NoSQL Databases.

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Here is my seminar presentation on No-SQL Databases. it includes all the types of nosql databases, merits & demerits of nosql databases, examples of nosql databases etc.
For seminar report of NoSQL Databases please contact me: ndc@live.in

Here is my seminar presentation on No-SQL Databases. it includes all the types of nosql databases, merits & demerits of nosql databases, examples of nosql databases etc.
For seminar report of NoSQL Databases please contact me: ndc@live.in

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A Seminar on NoSQL Databases.

  1. 1. NOSQL DATABASES Navdeep Charan MCA VI Semester
  2. 2. Contents  Introduction  What is NoSQL  Need of NoSQL  NoSQL Database Types  ACIDs & BASEs  CAP Theorem  Advantages of NoSQL  What is not provided by NoSQL  Where to use NoSQL  Conclusion  References 2/22
  3. 3. Introduction 30, 40 years history of well-established database technology… all in vain? Not at all! But both setups and demands have drastically changed:  main memory and CPU speed have exploded, compared to the time when System R (the mother of all RDBMS) was developed.  at the same time, huge amounts of data are now handled in real-time.  both data and use cases are getting more and more dynamic.  social networks (relying on graph data) have gained impressive momentum.  full-texts have always been treated shabbily by relational DBMS. 3/22
  4. 4. What is NoSQL?  Stands for Not Only SQL. Term was redefined by Eric Evans after Carlo Strozzi.  Class of non-relational data storage systems.  Do not require a fixed table schema nor do they use the concept of joins.  Relaxation for one or more of the ACID properties (Atomicity, Consistency, Isolation, Durability) using CAP theorem. Wikipedia’s Definition:  “A NoSQL database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases." 4/22
  5. 5. Need of NoSQL  Explosion of social media sites (Facebook, Twitter, Google etc.) with large data needs. (Sharding is a problem)  Rise of cloud-based solutions such as Amazon S3. (simple storage solution)  Just as moving to dynamically-typed languages (Ruby/Groovy), a shift to dynamically-typed data with frequent schema changes.  Expansion of Open-source community.  NoSQL solution is more acceptable to a client now than a year ago. 5/22
  6. 6. NoSQL Database Types NoSQL database are classified into four types:  Key Value pair based.  Column based.  Document based.  Graph based. 6/22
  7. 7. NoSQL Database Types (Key Value pair based)  Designed for processing dictionary. Dictionaries contain a collection of records having fields containing data.  Records are stored and retrieved using a key that uniquely identifies the record, and is used to quickly find the data within the database. Example: CouchDB, Oracle NoSQL Database, Riak etc. We use it for storing session information, user profiles, preferences, shopping cart data. We would avoid it when we need to query data having relationships between entities. 7/22
  8. 8. Contd. 8/22
  9. 9. NoSQL Database Types (Column based) We use it for content management systems, blogging platforms, log aggregation. We would avoid it for systems that are in early development, changing query patterns.  It store data as Column families containing rows that have many columns associated with a row key. Each row can have different columns.  Column families are groups of related data that is accessed together. Example: Cassandra, HBase, Hypertable, and Amazon DynamoDB. 9/22
  10. 10. Contd. 10/22
  11. 11. NoSQL Database Types (Document based)  The database stores and retrieves documents. It stores documents in the value part of the key-value store.  Self- describing, hierarchical tree data structures consisting of maps, collections, and scalar values. Example: Lotus Notes, MongoDB, Couch DB, Orient DB, Raven DB. We use it for content management systems, blogging platforms, web analytics, real- time analytics, e- commerce applications. We would avoid it for systems that need complex transactions spanning multiple operations or queries against varying aggregate structures. 11/22
  12. 12. Contd. 12/22
  13. 13. NoSQL Database Types (Graph based)  Store entities and relationships between these entities as nodes and edges of a graph respectively. Entities have properties.  Traversing the relationships is very fast as relationship between nodes is not calculated at query time but is actually persisted as a relationship. Example: Neo4J, Infinite Graph, OrientDB, FlockDB. It is well suited for connected data, such as social networks, spatial data, routing information for goods and supply. 13/22
  14. 14. Contd. 14/22
  15. 15. ACIDs & BASEs  Basically Available  system seems to work all the time.  Soft State  it doesn’t have to be consistent all the time.  Eventually Consistent  becomes consistent at some later time.  Atomic  a transaction is all or nothing.  Consistent  only valid data is written to the database.  Isolated  pretend all transactions are happening serially and the data is correct.  Durable  what you write is what you get. 15/22
  16. 16. CAP Theorem  According to Eric Brewer a distributed system has 3 properties:  Consistency  Availability  Partitions  We can have at most two of these three properties for any shared-data system.  To scale out, we have to partition. It leaves a choice between consistency and availability. (In almost all cases, we would choose availability over consistency)  Everyone who builds big applications builds them on CAP : Google, Yahoo, Facebook, Amazon, eBay, etc. 16/22
  17. 17. Advantages of NoSQL  Cheap and easy to implement. (open source)  Data are replicated to multiple nodes (therefore identical and fault tolerant) and can be partitioned.  When data is written, the latest version is on at least one node and then replicated to other nodes.  No single point of failure.  Easy to distribute.  Don't require a schema. 17/22
  18. 18. What is not provided by NoSQL?  Joins  Group by  ACID transactions  SQL  Integration with applications that are based on SQL 18/22
  19. 19. Where to use NoSQL?  NoSQL Data storage systems makes sense for applications that process very large semi-structured data –like Log Analysis, Social Networking Feeds, Time-based data.  To improve programmer productivity by using a database that better matches an application's needs.  To improve data access performance via some combination of handling larger data volumes, reducing latency, and improving throughput. 19/22
  20. 20. Conclusion  All the choices provided by the rise of NoSQL databases does not mean the demise of RDBMS databases as Relational databases are a powerful tool.  We are entering an era of Polyglot persistence, a technique that uses different data storage technologies to handle varying data storage needs. It can apply across an enterprise or within an individual application.  It’s about choosing right tool for right job. 20/22
  21. 21. References  “NoSQL Databases: An Overview”. Pramod Sadalage, thoughtworks.com.  “Data management in cloud environments: NoSQL and NewSQL data stores”. Katarina Grolinger, Wilson A Higashino, Abhinav Tiwari, Miriam AM Capretz.  “Making the Shift from Relational to NoSQL”. Couchbase.com.  “NoSQL - Death to Relational Databases”. Scofield, Ben.  https://blogs.msdn.microsoft.com/usisvde/2012/04/05/getting-acquainted-with- nosql-on-windows-azure/ 21/22
  22. 22. THANK YOU M.B.M. Government Engineering College, Jodhpur 22/22

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