Introduction to NOSQL quadrants
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NOSQL databases provide flexible, scalable alternatives to traditional relational databases. The main types of NOSQL databases are document stores, key-value stores, column family stores, and graph databases. Each has different data models and capabilities such as horizontal scaling, limited transactions, and using relationships as an index.
Introduction to NOSQL quadrants
- 2. NOSQL DATABASES • A cheeky acronym for Not Only SQL • More confrontationally, No to SQL.
- 3. THE RISE OF NOSQL DATABASES
- 4. TYPES OF NOSQL DATABASES
- 5. DOCUMENT STORES • Reply on indexes to facilitate access to documents based on their attributes.
- 6. DOCUMENT STORES • Data model of a document store is one of disconnected entities • Should scale horizontally, as there’s no contended state between mutually independent records at write time • Limitation:Transactions are limited to the level of an individual record. • Support for operating across sets of documents atomically is emerging
- 7. KEYVALUE STORES • Large, distributed hash map data structures that store and retrieve opaque values by key • Level of insight offered into data is due to data opacity. • To retrieve insight across individual records, a cluster computing framework like Map reduce or spark is used.
- 8. KEY-VALUE STORES 1.Key = Domain specific identifier 2.Key is hashed with a uniform distribution hash function. 3.Hashed key is used to store values in a corresponding bucket. 4.A similar procedure is used to retrieve data. 5.For fault tolerance each bucket is replicated onto several machines.
- 9. COLUMN FAMILY • Modelled on Google’s BigTable. • Logically speaking, it’s just a map of maps.
- 10. COLUMN FAMILY • Simplest storage unit: Column consisting of name value pair. • Super column: Sorted set of columns with a name.
- 11. COLUMN FAMILY • Columns are stored in rows, and when a row contains columns only, it is known as a column family. • When a row contains super columns, it is known as a super column family.
- 12. COLUMN FAMILY • In a column family database, each row in the table represents a particular overarching entity. They are containers for related pieces of data.
- 13. COLUMN FAMILY • Where each row gives a complete view of one entity, the column view naturally indexes particular aspects across the whole dataset.
- 14. GRAPH DATABASES • It contains nodes and relationships. • Nodes contain properties (key- value pairs). • Nodes can be labeled with one or more labels. • Relationships are named and directed, and always have a start and end node. • Relationships can also contain properties.
- 15. GRAPH DATABASES • Don’t depend heavily on indexes because the graph itself provides a natural adjacency index • Relationships attached to a node naturally provide a direct connection to other related nodes of interest. • Graph queries use this locality to traverse through the graph by chasing pointers.