NoSQL = Not Only SQL

ACID - Atomic, Consistent, Isolated, Durable

BASE - Basic Availability, Soft-state, Eventual consistency

CAP Theroem

  • Consistency: Every read receives the most recent value
  • Availability: Every request receives a (non-error) response without the guarantee that it contains the most recent write. no downtime.
  • Partition Tolerance: The system continues to operate despite an arbitrary number of nodes being dropped.

cap

NoSQL Database

Key-value Store Column Store Document Store Graph Store
Usage - image stores
- Key-tased file systems
- Object cache
- System designed to scale		 - Web crawler results
- Big data problem with relaxed consistency riles		 - High variability data
- Document search
- Web content management
- Publishing		 - Social network
- Fraud detection
- Relationship heavy data
Example Memcache Redis Riak Hbase Cassandra Hypertable MongoDB CoutchDB CouchBase Neo4J InfinteGraph(Objectively)

NoSQL Models: Key/Value Systems

  • A store of two fields: (Key, Value) pairs.
  • Only one way to access the data through hashing(Key) = value
  • No query language: only get/put/delete/update
  • Limited multi-record transactional consistency
  • Each row has timestemp

API

  • lookup(key) -> value
  • lookup(key range) -> value
  • getNext -> value
  • insert(key, value)
  • delete(key)

Use Cases

  • Storing data for customer preferences and profiles
  • Customized product recommendations, Ads, coupons
  • User profiles
  • Using cache to accelerate application responses
  • As a cache for heavily accessed but rarely updated data

NoSQL Models: Column Store

  • Motivated by Google’s BigTable
  • Extension of the K/V system, where columns can have a complex structure, rather than a blob value
  • Supports complex modeling structure (nested tables, repeating groups, set, list, etc.)
  • Big Table, Cassandra, HBase, Vertica, Accumulo, Hypertable, etc

NoSQL Models: Document Store

  • Similar to Key-value store, but the value is a complete document, such as JSON, XML, etc.
  • Any collection of documents such as maps, collections, and scalar values.

NoSQL Models: Graph Databases

  • Models data in terms of nodes and connections
  • Useful for inter-connected data such as communication patterns, social networks, bio interactions.
  • Allows us to ask deeper and more complex questions
  • Difficult to distribute components of a graph among a network of servers as graphs become larger.

Summary

Advantages Disadvantages
- Utilize the scale-out architecture that supports scalability, fault tolerance, and high availability
- Rapid insertion of arbitrary heterogeneous data with schema-on-read
- High performance of sequential scan (good for batch-oriented job such as OLAP workload)		 - Lack of ACID - Not adequate for OLTP workload that requires random access and ACID
- Lack of high-level functionality such as SQL, schemas, and secondary indexes