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  1. Stackups
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  4. Databases
  5. Memcached vs Varnish

Memcached vs Varnish

OverviewComparisonAlternatives

Overview

Memcached
Memcached
Stacks7.9K
Followers5.7K
Votes473
GitHub Stars14.0K
Forks3.3K
Varnish
Varnish
Stacks12.6K
Followers2.7K
Votes370
GitHub Stars887
Forks195

Memcached vs Varnish: What are the differences?

Introduction

In this article, we will discuss the key differences between Memcached and Varnish, two popular caching systems used in website optimization.

  1. Scalability: Memcached is a distributed caching system that allows for horizontal scalability by adding more servers to the cache pool. It uses a hash-based algorithm for storing and retrieving data, making it suitable for large-scale applications. On the other hand, Varnish is a reverse proxy cache that can handle high traffic loads and improve website performance by caching static content. It is designed to be deployed in front of web servers and can be scaled vertically by increasing hardware resources.

  2. Caching Mechanism: Memcached is a key-value cache that stores data in memory, enabling fast data retrieval. It is commonly used to cache database query results, API responses, and other frequently accessed data. Varnish, on the other hand, caches entire HTTP responses, including HTML pages, images, and CSS files. It uses an advanced caching mechanism that takes into account headers and cookies to determine if a resource can be served from cache or needs to be retrieved from the backend.

  3. Purging and Invalidation: Memcached does not provide built-in mechanisms for purging or invalidating cached data. To remove data from the cache, the application needs to explicitly overwrite or delete the corresponding key-value pair. In contrast, Varnish allows for granular control over cache invalidation. It provides a flexible configuration language that enables cache purging based on different criteria such as URL, HTTP method, or response headers. This makes Varnish more suitable for dynamic websites that frequently update their content.

  4. Content Delivery Network (CDN) Support: Memcached does not have native support for CDN integration. It primarily focuses on caching data within a distributed cluster of servers. Varnish, on the other hand, can be used as a front-end cache for a CDN. It can sit between the CDN edge servers and the origin servers, caching frequently accessed content at the edge locations and reducing the load on the backend infrastructure.

  5. Request Processing: Memcached operates at the transport layer (Layer 4) of the OSI model and does not parse or modify the content of the requests or responses. It simply stores and retrieves data based on the provided key. Varnish, on the other hand, functions at the application layer (Layer 7) and provides advanced features like request rewriting, header manipulation, and load balancing. It can be configured to modify request and response headers, route traffic to different backend servers, and perform other custom actions.

  6. Community and Ecosystem: Memcached has a large and active community of users and developers. It is widely used and supported by many programming languages and frameworks. Integration with applications is straightforward, and there is ample documentation available. Varnish also has a thriving community but is more commonly used in specific use cases, such as content-heavy websites or as a cache in front of web servers. It offers a range of extensions and modules, but its ecosystem is not as extensive as that of Memcached.

In summary, Memcached and Varnish differ in their scalability approaches, caching mechanisms, cache invalidation capabilities, CDN support, request processing abilities, and community ecosystems. Understanding these differences is crucial in selecting the appropriate caching system for specific use cases.

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Detailed Comparison

Memcached
Memcached
Varnish
Varnish

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

Varnish Cache is a web application accelerator also known as a caching HTTP reverse proxy. You install it in front of any server that speaks HTTP and configure it to cache the contents. Varnish Cache is really, really fast. It typically speeds up delivery with a factor of 300 - 1000x, depending on your architecture.

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Powerful, feature-rich web cache;HTTP accelerator; Speed up the performance of your website and streaming services
Statistics
GitHub Stars
14.0K
GitHub Stars
887
GitHub Forks
3.3K
GitHub Forks
195
Stacks
7.9K
Stacks
12.6K
Followers
5.7K
Followers
2.7K
Votes
473
Votes
370
Pros & Cons
Pros
  • 139
    Fast object cache
  • 129
    High-performance
  • 91
    Stable
  • 65
    Mature
  • 33
    Distributed caching system
Cons
  • 2
    Only caches simple types
Pros
  • 104
    High-performance
  • 67
    Very Fast
  • 57
    Very Stable
  • 44
    Very Robust
  • 37
    HTTP reverse proxy

What are some alternatives to Memcached, Varnish?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

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