Cassandra vs Memcached

Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

Memcached

Stacks7.9K

Followers5.7K

Votes473

GitHub Stars14.0K

Forks3.3K

Cassandra vs Memcached: What are the differences?

Key Differences between Cassandra and Memcached

Cassandra and Memcached are both popular distributed database systems, but they have several key differences.

Data Model:
- Cassandra: Cassandra is a wide column store database, which means that it organizes data into rows and columns similar to a traditional relational database.
- Memcached: Memcached is a key-value store database, where data is stored and retrieved based on unique keys.
Data Persistence:
- Cassandra: Cassandra supports data persistence, which means that data is stored permanently on disk even after a system failure or shutdown.
- Memcached: Memcached does not provide data persistence. Data is stored in-memory only and is lost upon system failure or shutdown.
Scalability:
- Cassandra: Cassandra is designed to scale horizontally, meaning that it can handle large volumes of data and high traffic loads by adding more machines to the cluster.
- Memcached: Memcached is primarily designed to scale vertically, meaning that it can handle higher traffic loads by adding more resources (CPU, RAM) to a single machine.
Data Distribution:
- Cassandra: Cassandra uses a peer-to-peer distributed architecture and employs a distributed hash table to evenly distribute data across multiple nodes in a cluster.
- Memcached: Memcached uses a client-server architecture, where data is distributed based on a hash function across multiple server instances.
Consistency Model:
- Cassandra: Cassandra offers tunable consistency levels, allowing the user to choose between strong consistency and eventual consistency based on their specific needs.
- Memcached: Memcached does not provide consistency guarantees. It focuses on providing high-speed data retrieval and caching.
Query Language:
- Cassandra: Cassandra uses its own query language called CQL (Cassandra Query Language), which is similar to SQL and provides a powerful set of features for data manipulation and retrieval.
- Memcached: Memcached does not have a query language. Data can only be accessed by specifying the key associated with the desired value.

In summary, Cassandra is a wide column store database with support for data persistence, horizontal scalability, and offers tunable consistency levels, while Memcached is a key-value store database without data persistence, focuses on vertical scalability, and does not provide consistency guarantees.

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Advice on Cassandra, Memcached

Micha

CEO & Co-Founder at Dechea

May 27, 2022

Decided

Fauna is a serverless database where you store data as JSON. Also, you have build in a HTTP GraphQL interface with a full authentication & authorization layer. That means you can skip your Backend and call it directly from the Frontend. With the power, that you can write data transformation function within Fauna with her own language called FQL, we're getting a blazing fast application.

Also, Fauna takes care about scaling and backups (All data are sharded on three different locations on the globe). That means we can fully focus on writing business logic and don't have to worry anymore about infrastructure.

93k views93k

Comments

Krishna Chaitanya

Head of Technology at Adonmo

Jun 27, 2021

Review

For such a more realtime-focused, data-centered application like an exchange, it's not the frontend or backend that matter much. In fact for that, they can do away with any of the popular frameworks like React/Vue/Angular for the frontend and Go/Python for the backend. For example uniswap's frontend (although much simpler than binance) is built in React. The main interesting part here would be how they are able to handle updating data so quickly. In my opinion, they might be heavily reliant on realtime processing systems like Kafka+Kafka Streams, Apache Flink or Apache Spark Stream or similar. For more processing heavy but not so real-time processing, they might be relying on OLAP and/or warehousing tools like Cassandra/Redshift. They could have also optimized few high frequent queries using NoSQL stores like mongodb (for persistance) and in-memory cache like Redis (for further perfomance boost to get millisecond latencies).

53.8k views53.8k

Comments

Umair

Technical Architect at ERP Studio

Feb 12, 2021

Needs adviceon

PostgreSQL

TimescaleDB

Druid

Developing a solution that collects Telemetry Data from different devices, nearly 1000 devices minimum and maximum 12000. Each device is sending 2 packets in 1 second. This is time-series data, and this data definition and different reports are saved on PostgreSQL. Like Building information, maintenance records, etc. I want to know about the best solution. This data is required for Math and ML to run different algorithms. Also, data is raw without definitions and information stored in PostgreSQL. Initially, I went with TimescaleDB due to PostgreSQL support, but to increase in sites, I started facing many issues with timescale DB in terms of flexibility of storing data.

My major requirement is also the replication of the database for reporting and different purposes. You may also suggest other options other than Druid and Cassandra. But an open source solution is appreciated.

462k views462k

Comments

Detailed Comparison

Cassandra	Memcached
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.	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.
Statistics
GitHub Stars 9.5K	GitHub Stars 14.0K
GitHub Forks 3.8K	GitHub Forks 3.3K
Stacks 3.6K	Stacks 7.9K
Followers 3.5K	Followers 5.7K
Votes 507	Votes 473
Pros & Cons
Pros 119 Distributed 98 High performance 81 High availability 74 Easy scalability 53 Replication Cons 3 Reliability of replication 1 Size 1 Updates	Pros 139 Fast object cache 129 High-performance 91 Stable 65 Mature 33 Distributed caching system Cons 2 Only caches simple types

What are some alternatives to Cassandra, Memcached?

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

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

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.

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 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

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 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.

CouchDB

Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.

Related Comparisons

Cassandra vs Memcached: What are the differences?

Key Differences between Cassandra and Memcached

Cassandra and Memcached are both popular distributed database systems, but they have several key differences.

Data Model:
- Cassandra: Cassandra is a wide column store database, which means that it organizes data into rows and columns similar to a traditional relational database.
- Memcached: Memcached is a key-value store database, where data is stored and retrieved based on unique keys.
Data Persistence:
- Cassandra: Cassandra supports data persistence, which means that data is stored permanently on disk even after a system failure or shutdown.
- Memcached: Memcached does not provide data persistence. Data is stored in-memory only and is lost upon system failure or shutdown.
Scalability:
- Cassandra: Cassandra is designed to scale horizontally, meaning that it can handle large volumes of data and high traffic loads by adding more machines to the cluster.
- Memcached: Memcached is primarily designed to scale vertically, meaning that it can handle higher traffic loads by adding more resources (CPU, RAM) to a single machine.
Data Distribution:
- Cassandra: Cassandra uses a peer-to-peer distributed architecture and employs a distributed hash table to evenly distribute data across multiple nodes in a cluster.
- Memcached: Memcached uses a client-server architecture, where data is distributed based on a hash function across multiple server instances.
Consistency Model:
- Cassandra: Cassandra offers tunable consistency levels, allowing the user to choose between strong consistency and eventual consistency based on their specific needs.
- Memcached: Memcached does not provide consistency guarantees. It focuses on providing high-speed data retrieval and caching.
Query Language:
- Cassandra: Cassandra uses its own query language called CQL (Cassandra Query Language), which is similar to SQL and provides a powerful set of features for data manipulation and retrieval.
- Memcached: Memcached does not have a query language. Data can only be accessed by specifying the key associated with the desired value.

Cassandra vs Memcached

Overview

Cassandra vs Memcached: What are the differences?