NoSQL: Difference between revisions
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Document databases are conceptually similar to Google [[Bigtable]] database. The data model allows rows that can be added with any set of columns, and the columns do not need to be predefined. The lack of predefined schema makes these databases attractive for applications where the attributes of objects are not known in advance or change frequently. | Document databases are conceptually similar to Google [[Bigtable]] database. The data model allows rows that can be added with any set of columns, and the columns do not need to be predefined. The lack of predefined schema makes these databases attractive for applications where the attributes of objects are not known in advance or change frequently. | ||
* Google [[Bigtable]] | * Google [[Bigtable]] | ||
* [[Cassandra]] | ** [[Cassandra]] | ||
* [[HBase]] | ** [[HBase]] | ||
** Hypertable | |||
==Graph Databases== | ==Graph Databases== | ||
Revision as of 22:33, 7 November 2021
Internal
Overview
The NoSQL databases are grouped in four categories:
- document stores
- key-value stores
- graph stores
- column stores
NoSQL Databases
Document Databases
Document databases are conceptually similar to Google Bigtable database. The data model allows rows that can be added with any set of columns, and the columns do not need to be predefined. The lack of predefined schema makes these databases attractive for applications where the attributes of objects are not known in advance or change frequently.
Graph Databases
- CouchDB
- Neo4j
- Amazon DynamoDB
Organizatorium
- NoSQL discussion: https://bigdata-ir.com/wp-content/uploads/2017/04/NoSQL-Distilled.pdf NoSQL Distilled by Sadalage, Fowler. (Learning/Systems Design)
- Should you go Beyond Relational Databases? https://blog.teamtreehouse.com/should-you-go-beyond-relational-databases
- Lack of predefined schema.