Types Of No Sql
Exploring Different Types of NoSQL Databases
Types Of No Sql
NoSQL databases are utilized for managing a large volume of unstructured or semi-structured data, offering flexibility and scalability that traditional SQL databases may lack. Types of NoSQL databases include document stores, key-value stores, column stores, and graph databases, each offering unique advantages for different use cases. For example, document stores like MongoDB are ideal for storing and retrieving complex hierarchical data, while key-value stores like Redis are efficient for simple lookups and caching. By choosing the right type of NoSQL database, organizations can better handle varying data structures and volumes to ensure high performance and scalability for their applications.
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1 - Document based databases:
Document based databases store information in the form of documents, typically using formats like JSON or BSON.
2) Key value stores:
Key value stores are designed to store data as a collection of key value pairs, enabling efficient retrieval and storage of data.
3) Column family stores:
Column family stores store data in columns rather than rows, making them well suited for analytical workloads and time series data.
4) Graph databases:
Graph databases are designed to represent and store data in nodes and edges, making them ideal for applications that require complex relationship mapping.
5) Object oriented databases:
Object oriented databases store data in objects, allowing for easier representation and manipulation of data.
6) Time series databases:
Time series databases are optimized for handling time stamped data and are commonly used in applications like IoT, financial services, and monitoring systems.
7) Wide column stores:
Wide column stores store data in columns grouped together as column families, making them suitable for read and write heavy workloads.
8) Document store databases:
Document store databases store data in flexible, schema less documents, making them ideal for applications with evolving data requirements.
9) Eventual consistency:
NoSQL databases often prioritize availability and partition tolerance over strict consistency, providing eventual consistency where data may take time to synchronize across nodes.
10) Horizontal scalability:
NoSQL databases are designed for horizontal scalability, allowing them to easily scale out by adding more nodes to the database cluster.
11) CAP theorem:
The CAP theorem states that a distributed system can only achieve two out of three attributes: Consistency, Availability, and Partition tolerance. NoSQL databases are often designed with this theorem in mind.
12) Polyglot Persistence:
NoSQL databases enable polyglot persistence, where different types of databases can be used in combination to store different types of data based on their specific requirements.
13) ACID properties:
Unlike traditional relational databases that adhere to ACID properties (Atomicity, Consistency, Isolation, Durability), NoSQL databases may sacrifice some of these properties in favor of performance and scalability.
14) Use cases:
NoSQL databases are commonly used in applications requiring high availability, fast scalability, real time analytics, content management systems, and more.
15) Training program:
A comprehensive training program on NoSQL databases should cover the various types of NoSQL databases, their characteristics, use cases, advantages, and limitations. It should include hands on experience with popular NoSQL databases like MongoDB, Cassandra, Redis, and Neo4j. Additionally, practical exercises, case studies, and real world applications should be included to provide students with a holistic understanding of NoSQL databases and their role in modern data management.
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