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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Clickhouse vs Memcached

Clickhouse vs Memcached

OverviewComparisonAlternatives

Overview

Memcached
Memcached
Stacks7.9K
Followers5.7K
Votes473
GitHub Stars14.0K
Forks3.3K
Clickhouse
Clickhouse
Stacks431
Followers543
Votes85

Clickhouse vs Memcached: What are the differences?

Introduction

ClickHouse and Memcached are two widely used technologies in the field of data storage and caching. While they serve different purposes, it is important to understand the key differences between them before deciding which one to use in a specific scenario.

  1. Data Storage: ClickHouse is a column-oriented DBMS specifically designed for analytics and handling large volumes of data. It provides efficient storage and retrieval of structured and semi-structured data. On the other hand, Memcached is an in-memory key-value store that is primarily used for caching and speeding up data access.

  2. Data Structure: ClickHouse stores data in a columnar format where each column is stored separately, enabling fast data compression and efficient query processing for analytical workloads. In contrast, Memcached stores data in a simple key-value format, where each value is associated with a unique key. This makes it suitable for caching small pieces of data that are frequently accessed.

  3. Querying Capabilities: ClickHouse supports a wide range of analytical functions and querying capabilities, including standard SQL queries and complex aggregations. It provides powerful tools for data analysis, such as filtering, grouping, and joining. On the other hand, Memcached does not provide any built-in querying capabilities. It simply allows you to store and retrieve data based on a specific key.

  4. Persistence: ClickHouse provides persistent storage, which means data is durable and can be stored on disk even after a server restart. This feature ensures data integrity and enables long-term data retention. In contrast, Memcached is an in-memory cache and does not support data persistence. Data stored in Memcached is lost when the server restarts or shuts down.

  5. Scalability: ClickHouse is designed to handle large volumes of data and can scale horizontally by adding more servers to a cluster. It provides automatic data distribution and replication, ensuring high availability and fault tolerance. On the other hand, Memcached is a single-threaded server and can only scale vertically by adding more resources to the existing server.

  6. Data Lifespan: ClickHouse is typically used for storing historical data and is suitable for long-term storage and analysis. It is optimized for handling immutable data that rarely changes. On the other hand, Memcached is used for caching frequently accessed data that has a short lifespan. It is suitable for data that is temporary and can be regenerated or fetched from a persistent data source.

In Summary, ClickHouse is a column-oriented DBMS designed for large-scale analytics, providing powerful querying capabilities and data persistence. Memcached, on the other hand, is a key-value store used for caching frequently accessed data with a short lifespan.

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Detailed Comparison

Memcached
Memcached
Clickhouse
Clickhouse

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.

It allows analysis of data that is updated in real time. It offers instant results in most cases: the data is processed faster than it takes to create a query.

Statistics
GitHub Stars
14.0K
GitHub Stars
-
GitHub Forks
3.3K
GitHub Forks
-
Stacks
7.9K
Stacks
431
Followers
5.7K
Followers
543
Votes
473
Votes
85
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
  • 21
    Fast, very very fast
  • 11
    Good compression ratio
  • 7
    Horizontally scalable
  • 6
    Utilizes all CPU resources
  • 5
    RESTful
Cons
  • 5
    Slow insert operations

What are some alternatives to Memcached, Clickhouse?

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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