Distribution Models in NoSQL Databases
1. Introduction
A distribution model defines how data and workload are distributed across servers in a database system.
NoSQL databases use different distribution models to achieve scalability, availability, and fault tolerance.
2. Single Server Model
Definition
In the single server model, all data and processing are handled by one server.
Features
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Simple architecture
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Easy to manage
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No data distribution
Advantages
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Easy setup
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Low complexity
Limitations
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Limited scalability
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Single point of failure
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Not suitable for big data
Use Case
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Small applications
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Development and testing
3. Master–Slave Replication Model
Definition
One server acts as master and handles all write operations, while other servers act as slaves and replicate data from the master.
Features
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Master handles writes
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Slaves handle reads
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Data replication is used
Advantages
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Improved read performance
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High availability
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Data backup
Limitations
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Master is a single point of failure
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Write scalability is limited
Examples
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MongoDB (Replica Set)
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MySQL replication
4. Peer-to-Peer (P2P) Replication Model
Definition
In the peer-to-peer model, all nodes are equal.
Each node can handle both read and write operations.
Features
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No master node
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Data distributed and replicated
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High fault tolerance
Advantages
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No single point of failure
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High scalability
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Better availability
Limitations
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Complex data consistency management
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Conflict resolution required
Examples
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Apache Cassandra
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Riak
5. Combining Sharding and Replication
Definition
This model combines data partitioning (sharding) with data replication.
Features
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Data is divided into shards
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Each shard is replicated across nodes
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Provides scalability and availability
Advantages
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Handles large datasets
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High fault tolerance
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Better performance
Examples
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MongoDB (Sharded clusters)
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Cassandra
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