no sql presentation
- 1. Presented by: Chandan Malik (801431006)
- 2. NO SQL- Non Relational Database • No SQL provides a mechanism for storage and retrieval of data that is modelled in means other than tabular relations.
- 3. Why Cloud Data Stores Explosion of social media sites (Facebook, Twitter) with large data needs Explosion of storage needs in large web sites such as Google, Yahoo Much of the data is not files Rise of cloud-based solutions such as Amazon S3 (simple storage solution) Shift to dynamically-typed data with frequent schema changes
- 4. Scaling Best way to provide ACID and a rich query model is to have the dataset on a single machine RDBMS were not designed to be distributed As database grows, rate of number of transactions per second falls. One solution is partitioning of large tables that is to scale out the database across a cluster of separate database servers.
- 5. What is No SQL ? Stands for Not Only SQL Class of non-relational data storage systems Usually do not require a fixed table schema Do not use the concept of joins which are expensive operations. Lack ACID ( Atomicity, Consistency, Isolation, Durability) properties. Leading users of NoSQL datastores are social networking sites such as Twitter, Facebook, LinkedIn It's not a replacement for a RDBMS but compliments it
- 6. CAP Theorem CAP theorem states that it is impossible for any shared data system to simultaneously hold these three properties: 1. Consistency ( all nodes see same data at the same time) 2. Availability ( guarantee that every request receives a response ) 3. Partition ( Partitioning or distributing the database) You can have at most two of these three properties
- 7. CAP Theorem To scale out, you have to partition. That leaves either consistency or availability to choose from, Choose a specific approach based on the needs of the service. CAP Theorem states: Strict Consistency can't be achieved at the same time as availability and partition-tolerance. When no updates occur for a long period of time, eventually all updates will propagate through the system and all the nodes will be eventually consistent
- 8. BASE Scalability and better performance of No SQL is achieved by sacrificing ACID properties. No SQL is having BASE compatibility BA – Basically available S – Soft State E- Eventually consistent 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
- 9. Types of No Sql databases 1. Key-value data model 2. Document-data model 3. Column family data model 4. Graph data model
- 10. Key-Value Data model It has a Big Hash Table of keys & values
- 11. Key-Value Data model The key can be auto-generated while the value can be String, JSON, BLOB (basic large object) etc This key/value type database allow clients to read and write values using the key as follows: 1. get(key) -- Extract the value given a key 2. put(key, value) -- Create or update the value given its key 3. delete(key) -- Remove the key and its associated value 4. execute(key, operation, parameters) -- Invoke an operation to the value (given its key) which is a special data structure (e.g. List, Set, Map .... etc).
- 12. Key-Value Data model Performance is enhanced to a great degree because of the cache mechanisms that accompany the mappings Eg: Amazon DynamoDB is a fully managed proprietary No SQL database service that is offered by Amazon.com as part of the Amazon Web Services portfolio
- 13. No SQL distinguishing Characteristics Suitable for applications that supports large amount of unstructured data. Schema-less Do not support Joins Do not follow ACID properties Scalable Data is replicated to multiple nodes (therefore identical and fault-tolerant) and can be partitioned
- 14. THANK YOU