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HomeHomework Helpcomputer-scienceDatabase Scaling Techniques

Database Scaling Techniques

Methods used to increase the capacity of a database to handle growing amounts of data and user requests, including sharding, which involves dividing and distributing data across multiple servers, and vertical scaling, which involves increasing the computing power and memory of individual servers

intermediate
3 hours
Computer Science
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Overview

Database scaling techniques are essential for managing increasing data loads and user demands. By understanding the differences between vertical and horizontal scaling, as well as the importance of load balancing and sharding, developers can design systems that remain efficient and responsive. Each ...

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Key Terms

Vertical Scaling
Adding more resources (CPU, RAM) to a single server.

Example: Upgrading a server from 16GB to 64GB of RAM.

Horizontal Scaling
Adding more servers to handle increased load.

Example: Adding additional web servers to a cluster.

Load Balancer
A device or software that distributes network or application traffic across multiple servers.

Example: Using an NGINX server to balance requests between multiple application servers.

Database Sharding
Splitting a database into smaller, more manageable pieces called shards.

Example: Dividing user data by geographical location into different shards.

Throughput
The amount of data processed by a system in a given time.

Example: A database processing 1000 queries per second.

Latency
The time it takes for a request to travel from the client to the server and back.

Example: A 200ms delay in response time.

Related Topics

Cloud Computing
Understanding how cloud services can enhance database scalability.
intermediate
Database Replication
Exploring methods to create copies of databases for redundancy and performance.
intermediate
Microservices Architecture
Learning how microservices can impact database design and scaling.
advanced

Key Concepts

Vertical ScalingHorizontal ScalingLoad BalancingDatabase Sharding