Big data key-value and column stores redis - cassandra
Download as PPTX, PDF1 like673 views
The document provides an introduction to NoSQL database types, including key/value stores, column stores, document stores, and graph databases. It discusses the strengths and weaknesses of each type as well as common use cases. It also covers the CAP theorem, which states that a distributed system cannot simultaneously provide consistency, availability, and partition tolerance. The document establishes that different NoSQL database types adhere to different parts of the CAP theorem and provides examples for each. Setup instructions are also included to access code repositories for hands-on exercises with Cassandra and Redis.
Big data key-value and column stores redis - cassandra
- 1. Big Data NoSQL Database Types: episode I
- 2. Content ▪ Setup ▪ Introduction ▪ Key/Value ▪ Column Store
- 3. Setup 1. Go to https://github.com/tomvdbulck/cassandrainitiationsearchworkshop And https://github.com/tomvdbulck/redisinitiationsearchworkshop 2. Make sure the following items have been installed on your machine: o Java 7 or higher o Git (if you like a pretty interface to deal with git, try SourceTree) o Maven 3. Install VirtualBox https://www.virtualbox.org/wiki/Downloads 4. Install Vagrant https://www.vagrantup.com/downloads.html 5. Clone the repository into your workspace
- 4. Introduction ▪ 4 Types of NoSQL ▪ CAP Theorem
- 5. Types of NoSQL data stores Following 4 types exist ▪ Key/Value Store ▪ Column Store ▪ Document Store ▪ Graph Database
- 6. Types of NoSQL data stores Key/Value - key/value - are often “in-memory” - Strength ▪simple to implement ▪fast lookup - Weakness ▪querying ▪stored data has no schema - Use Case: ▪Caching ▪Top 10 list of facebook games
- 7. Types of NoSQL data stores Column Store: - Stores everything in columns - Strength ▪fast lookup ▪distributed storage of data ▪better querying then key/value - Weakness ▪low-level api ▪cumbersome to do more complex queryies - Use Case: ▪Distributed file system ▪(twitter, netflix)
- 8. Types of NoSQL data stores Document Store: - collections of key/value collections (documents) - Strength ▪Tolerant of incomplete data ▪Easier to do more complex queries - Weakness ▪Query performance - Use Case ▪standard web applications
- 9. Types of NoSQL data stores Graph Database - store everything in a graph - use of nodes - nodes have relations to adjacent nodes - no index lookup required - Strength ▪graph algorithms ▪visualize relations - Weakness ▪has to traverse entire graph to get answer ▪not easy to cluster - Use Case: ▪Social Networking ▪Recommendations
- 10. Types of NoSQL data stores
- 11. Types of NoSQL data stores Graph Database:
- 12. Types of NoSQL data stores Graph Database: playing around Visualize your own linkedin network: http://neo4j.com/blog/exploring-linkedin-in-neo4j/
- 13. Types of NoSQL data stores Which to use? ▪ Often you will be using more then one, based on which one is the best fit for specific requirements ▪ You could also use 1 for development - schemaless, pretty feature complete (document store) and when feature-complete choose more appropriate databases. => a modular architecture will be important when you develop like this
- 14. CAP Theorem Impossible for a distributed file system to simultaneously provide the following guarantees: ▪ Consistency: all nodes see the same data at the same time ▪ Availability: guarantee that every request receives a response about whether it succeeded or failed ▪ Partition Tolerance: the system continues to operate despite arbitrary message loss or failure of part of the system
- 15. CAP Theorem Consistency: When I ask the same question to any part of the system I should get the same answer.
- 16. CAP Theorem Consistency: When I ask the same question to any part of the system I should get the same answer.
- 17. CAP Theorem Consistency: When I ask the same question to any part of the system I should get the same answer.
- 18. CAP Theorem Availability: When I ask a question I will get an answer.
- 19. CAP Theorem Availability: When I ask a question I will get an answer.
- 20. CAP Theorem Partition Tolerance: I can ask questions even if the system is having intra-system communication problems
- 21. CAP Theorem Partition Tolerance: I can ask questions even if the system is having intra-system communication problems
- 22. CAP Theorem
- 23. CAP Theorem ▪ Consistent Available (CA): - have trouble with partitions and deal with it via replications - Examples: RDBMs ▪ Consistent, Partition-Tolerant (CP): - have trouble with availability while keeping data consistent across partitioned nodes - Examples: MongoDB, HBase,BigTable, HyperTable, Redis ▪ Available, Partition-Tolerant (AP) - achieve “eventual consistency” through replication and verification - Examples: CouchDB, Cassandra, Voldemort, Riak
- 24. Content ▪ Key/Value ▪ Column Store
- 25. Key/Value
- 26. Column Store