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Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
Introduction to no sql database
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Introduction to no sql database

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Introduction to NoSQL database and polyglot persistence

Introduction to NoSQL database and polyglot persistence

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Transcript

  • 1. NoSQL It’s about making intelligent choices
  • 2. The Relation Model • • • • • • • • • Simplicity and Elegance Well Understood Very Powerful Abstraction Solve Many Storage Problem (Persistent Data) Concurrency Integration A Mostly Standard Model … But It also has its Limitation…
  • 3. Business Database
  • 4. Issues With Implementing A Relational Database • Agility and Programmability (Impedance Mismatch) • Flexibility • Performance and Scalability • Availability
  • 5. NoSQL Business Drivers
  • 6. NoSQL No SQL Not Only SQL Non-relational Database
  • 7. Key/Value Store
  • 8. Typical Usage • Image Stores • Key-Based File Systems • Object Cache • Systems Designed to Scale
  • 9. Key/Value Store • • • • • • BerkeleyDB LevelDB Memcached Project Voldemort Redis Riak
  • 10. Document Database
  • 11. Typical Usage • Web Crawler Results • Big Data Problems That Can Relax Consistency Rules
  • 12. Document Database • • • • • CouchDB MongoDB OrientDB RavenDB Terrastore
  • 13. Column Family
  • 14. Typical Usage • • • • • High-Variability Data Document Search Integration Hubs Web Content Management Publishing
  • 15. Column Family • Amazon SimpleDB • Cassandra • Hbase • HyperTable
  • 16. Graph Database
  • 17. Typical Usage • Social Networks • Fraud Detection • Relationship-Heavy Data
  • 18. Graph Database • • • • • FlockDB HyperGraphDB InfiniteGraph Neo4J OrientDB
  • 19. Common Features of NoSQL Databases • Designing Aggregations • • Materializing Summary Data • • Sharding Improving Consistency • • Clusters Improving Scalability and Reducing Network Latency • • Map/Reduce Implementing High Availability • • An aggregate in a NoSQL database is similar to a row in a table in a relational database Data Versioning Schemas and Non-Uniformity
  • 20. NoSQL Case Studies
  • 21. LiveJournal’s Memcache
  • 22. LiveJournal’s Memcache • Driver • • Need to increase performance of database queries. Finding • By using hashing and caching, data in RAM can be shared. This cuts down the number of read requests sent to the database, increasing performance.
  • 23. Google’s MapReduce
  • 24. MapReduce Example – Word Count
  • 25. Google’s MapReduce • Driver • Need to index billions of web pages for search using low-cost hardware. • Finding • By using parallel processing, indexing billions of web pages can be done quickly with a large number of commodity processors.
  • 26. Google BigTable • Driver • Need to flexibly store tabular data in a distributed system. • Finding • By using a sparse matrix approach, users can think of all data as being stored in a single table with billions of rows and millions of columns without the need for up-front data modeling.
  • 27. Amazon’s Dynamo
  • 28. Amazon’s Dynamo • Driver • Need to accept a web order 24 hours a day, 7 days a week. • Finding • A key-value store with a simple interface can be replicated even when there are large volumes of data to be processed.
  • 29. Polyglot Persistence
  • 30. Key Points • • • • Relational databases have been a successful technology for twenty years, providing persistence, concurrency control, and an integration mechanism. Application developers have been frustrated with the impedance mismatch between the relational model and the in-memory data structures. There is a movement away from using databases as integration points towards encapsulating databases within applications and integrating through services. The most important result of the rise of NoSQL is Polyglot Persistence.
  • 31. Key Points • • • The vital factor for a change in data storage was the need to support large volumes of data by running on clusters. Relational databases are not designed to run efficiently on clusters. NoSQL is an accidental neologism. There is no prescriptive definition—all you can make is an observation of common characteristics. The common characteristics of NoSQL databases are • • • • • Not using the relational model Running well on clusters Open Source Built for the 21st century web estates Schemaless

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