Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

ArangoDB

Stacks273

Followers442

Votes192

ArangoDB vs Cassandra: What are the differences?

Introduction

When considering database management systems for a project, ArangoDB and Cassandra are two popular options. While both are NoSQL databases, they have key differences that should be considered before making a decision.

Data Model: ArangoDB is a multi-model database that supports key-value pairs, documents, and graphs within a single query interface, making it versatile for different data structures. On the other hand, Cassandra follows a column-family data model, which is ideal for handling large amounts of data with high availability and partition tolerance but may be more limited in terms of data structure flexibility.
Query Language: ArangoDB uses its query language, AQL (ArangoDB Query Language), which allows for complex queries across different data models. In contrast, Cassandra uses CQL (Cassandra Query Language), a SQL-like language that is optimized for querying high-volume, low-latency data.
Consistency Model: ArangoDB supports both strong and eventual consistency levels, giving users the flexibility to choose the level of consistency needed for their application. On the other hand, Cassandra offers tunable consistency, allowing users to choose between strong, eventual, and other consistency levels based on their requirements.
Scalability: ArangoDB is horizontally scalable, meaning it can distribute data across multiple nodes to handle growing amounts of data and traffic. Cassandra, on the other hand, is known for its linear scalability, making it a popular choice for large-scale distributed systems that require seamless scaling.
Fault Tolerance: ArangoDB provides automatic sharding and replication for data redundancy and fault tolerance, ensuring data availability even in the case of node failures. In comparison, Cassandra is designed with fault tolerance in mind, using a masterless architecture and peer-to-peer communication to prevent any single point of failure.
Use Cases: ArangoDB is suitable for applications that require flexibility in data modeling and complex queries across different data types, such as social networks and content management systems. In contrast, Cassandra is best suited for use cases that prioritize high availability, partition tolerance, and linear scalability, such as real-time analytics and messaging platforms.

In Summary, ArangoDB and Cassandra differ in aspects such as data model flexibility, query language, consistency levels, scalability options, fault tolerance mechanisms, and ideal use cases.

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Advice on Cassandra, ArangoDB

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

gitgkk

Oct 19, 2021

Needs adviceon

TinyMCE

JSON

ArangoDB

Hello All, I'm building an app that will enable users to create documents using ckeditor or TinyMCE editor. The data is then stored in a database and retrieved to display to the user, these docs can contain image data also. The number of pages generated for a single document can go up to 1000. Therefore by design, each page is stored in a separate JSON. I'm wondering which database is the right one to choose between ArangoDB and PostgreSQL. Your thoughts, advice please. Thanks, Kashyap

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Detailed Comparison

Cassandra	ArangoDB
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.	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.
-	multi-model nosql db; acid; transactions; javascript; database; nosql; sharding; replication; query language; joins; aql; documents; graphs; key-values; graphdb
Statistics
GitHub Stars 9.5K	GitHub Stars -
GitHub Forks 3.8K	GitHub Forks -
Stacks 3.6K	Stacks 273
Followers 3.5K	Followers 442
Votes 507	Votes 192
Pros & Cons
Pros 119 Distributed 98 High performance 81 High availability 74 Easy scalability 53 Replication Cons 3 Reliability of replication 1 Updates 1 Size	Pros 37 Grahps and documents in one DB 26 Intuitive and rich query language 25 Good documentation 25 Open source 21 Joins for collections Cons 3 Web ui has still room for improvement 2 No support for blueprints standard, using custom AQL

What are some alternatives to Cassandra, ArangoDB?

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.

Memcached

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.

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.

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.