Redis, MemCached, MongoDB comparison

Recently, I have been studying server performance optimization and high-concurrency request access, investigating unstructured data (NoSQL) and memory acceleration (Cache), and redesigning the old platform services, striving to save costs by US$10,000 per month.

The research projects mainly include Redis, MemCached, MongoDB, and Amazon’s DynamoDB

Redis is an open source ANSI
It is written in C language, supports network, can be memory-based and persistent log-type, Key-Value database, and provides APIs in multiple languages. The development work is currently hosted by VMware.

1) Data model
As a Key-value database, Redis also provides a mapping relationship between keys and values. In addition to regular numerical values ​​or strings, Redis key values ​​can also be in one of the following forms:
Lists
Sets
Sorted sets (ordered sets)
Hashes (hash table)
The data type of a key value determines the operations supported by the key value. Redis supports advanced atomic operations such as intersection, union, and difference of lists, sets, or ordered sets; at the same time, if the type of the key value is an ordinary number, Redis provides atomic operations such as increment.

2) Persistence:

Redis usually stores data in memory or is configured to use virtual memory.

Data persistence can be achieved in two ways: using snapshots to continuously write data in memory to disk; or using a log method similar to MySQL to record the log of each update. The former has higher performance, but may cause a certain degree of data loss; the latter has the opposite effect.

3) Performance synchronization:

Redis supports synchronizing data to multiple slave libraries, which is very beneficial to improving read performance. Compared with databases that rely on disk to record each update, the memory-based feature undoubtedly brings excellent performance to Redis, and there is a significant performance difference between read and write operations.

4) API language

Supports C, C++, C#, Java, Javascript, Lua, Objective-C, Perl, PHP, Python, Ruby, Go and other languages. For more information, please see: Redis
Official website

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Memcached is a high-performance distributed memory object caching system for dynamic web applications to reduce database load. It delivers the speed of dynamic, database-driven websites by caching data and objects in memory to reduce the number of database reads. Memcached is based on a hashmap that stores key/value pairs. Its daemon
) is written in C, but the client can be written in any language and communicates with the daemon via the memcached protocol.

1) Event handling

Memcached uses the libevent library and can exert its high performance on operating systems such as Linux, BSD, and Solaris. Libevent is a program library that encapsulates event processing functions such as Linux’s epoll and BSD-like operating system’s kqueue into a unified interface.

2) Data storage

In order to improve performance, the data saved in memcached is stored in memcached’s built-in memory storage space. Since data only exists in memory, restarting memcached and restarting the operating system will cause all data to disappear. In addition, after the content capacity reaches the specified value, the LRU (Least
Recently
Used (least recently used) algorithm automatically deletes unused caches. Memcached itself is a server designed for caching, so it does not consider the persistence of data too much.

3) API language

Support C, C#, C++,
Java, Perl, PHP, Python, Ruby, Lua and other languages, please see:
Memcached Clients

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MongoDB is a database based on distributed file storage, written in C++ language, designed to provide scalable, high-performance data storage solutions for WEB applications.

The MongoDB server can run on Linux, Windows or IOS platforms, supports 32-bit and 64-bit applications, and the default port is 27017. It is recommended to run on a 64-bit platform because the maximum file size supported by MongoDB when running in 32-bit mode is 2GB, which is very large on a 64-bit platform.

MongoDB is a product between a relational database and a non-relational database. It is the most feature-rich and most like a relational database among non-relational databases. The data structure it supports is very loose and is a bson format similar to json, so it can store more complex data types. The biggest feature of Mongo is that the query language it supports is very powerful. Its syntax is somewhat similar to an object-oriented query language. It can almost implement most functions similar to single-table queries in relational databases, and it also supports indexing of data.

1) Features: high performance, easy to deploy, easy to use, very convenient to store data

2)
Function: Oriented to collection storage, easy to store object type data; supports dynamic query, supports full index, including internal objects; supports replication and failure recovery; uses efficient binary data storage, including large objects (such as videos, etc.); automatically handles fragmentation , to support scalability at the cloud computing level

3) Format: The file storage format is BSON (an extension of JSON); it can be accessed through the network

4) API language: C, C#, C++, Java, Javascript,
PHP, Ruby, Python, Perl, etc. For more information, please see: MongoDB Home