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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. ArangoDB vs CouchDB

ArangoDB vs CouchDB

OverviewDecisionsComparisonAlternatives

Overview

CouchDB
CouchDB
Stacks529
Followers584
Votes139
GitHub Stars6.7K
Forks1.1K
ArangoDB
ArangoDB
Stacks273
Followers442
Votes192

ArangoDB vs CouchDB: What are the differences?

Introduction:

ArangoDB and CouchDB are both NoSQL databases that are designed to handle large amounts of data and provide high performance. However, there are key differences between the two that make them suitable for different use cases.

1. Data Model:

ArangoDB is a multi-model database, which means it supports multiple data models including document, graph, and key-value. It allows users to store and manage structured, semi-structured, and unstructured data in a single database. On the other hand, CouchDB is a document-oriented database that stores data in JSON format. It is specifically designed for handling semi-structured data and provides a simple and flexible storage model.

2. Query Language:

ArangoDB uses a query language called AQL (ArangoDB Query Language) for performing complex queries and data manipulation. AQL is a powerful language that supports a wide range of operations and allows users to combine document, graph, and key-value operations in a single query. In contrast, CouchDB uses map-reduce functions for querying and data transformation. Map-reduce allows users to define custom functions for extracting and processing data from documents.

3. Replication and Scalability:

ArangoDB supports both master-slave and active-passive replication, which allows users to create replicas of their data for fault tolerance and high availability. It also provides support for sharding, which enables horizontal scalability by distributing the data across multiple servers. On the other hand, CouchDB supports master-master replication, where the databases can sync with each other bidirectionally. This allows for decentralized data replication and enables offline access to data. However, CouchDB does not natively support sharding for horizontal scalability.

4. Licensing:

ArangoDB is licensed under the Apache 2.0 license, which allows users to freely download, use, and modify the software. It also allows for commercial use. CouchDB, on the other hand, is licensed under the Apache License 2.0 as well, but it has an additional term called the "Commons Clause". The Commons Clause restricts the commercial use of CouchDB and prohibits users from selling CouchDB as a service without obtaining a separate license.

5. Indexing:

ArangoDB supports various types of indexing including primary, secondary, hash, skiplist, and fulltext indexes. This allows for efficient searching and querying of data based on different criteria. CouchDB, on the other hand, only supports simple B-tree indexes on fields within the documents. While this is sufficient for many use cases, it may limit the flexibility and performance of complex queries.

6. Community and Ecosystem:

ArangoDB has a strong and active community with regular updates and contributions from the user community. It has a growing ecosystem of libraries, tools, and extensions that enhance its functionality. CouchDB also has an active community, but it is relatively smaller compared to ArangoDB. It has a mature ecosystem with various plugins and extensions, but it may not have as many options as ArangoDB.

In Summary, ArangoDB is a multi-model database with support for various data models, a powerful query language, and extensive indexing capabilities. It also provides advanced replication and scalability options. CouchDB, on the other hand, is a document-oriented database with a simple storage model, map-reduce queries, and decentralized replication. While both databases have their strengths, the choice between them depends on the specific use case and requirements.

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Advice on CouchDB, ArangoDB

Gabriel
Gabriel

CEO at Naologic

Jan 2, 2020

DecidedonCouchDBCouchDBCouchbaseCouchbaseMemcachedMemcached

We implemented our first large scale EPR application from naologic.com using CouchDB .

Very fast, replication works great, doesn't consume much RAM, queries are blazing fast but we found a problem: the queries were very hard to write, it took a long time to figure out the API, we had to go and write our own @nodejs library to make it work properly.

It lost most of its support. Since then, we migrated to Couchbase and the learning curve was steep but all worth it. Memcached indexing out of the box, full text search works great.

592k views592k
Comments
T
T

Feb 24, 2022

Decided

I’m newbie I was developing a pouchdb and couchdb app cause if the sync. Lots of learning very little code available. I dropped the project cause it consumed my life. Yeats later I’m back into it. I researched other db and came across rethinkdb and mongo for the subscription features. With socketio I should be able to create and similar sync feature. Attempted to use mongo. I attempted to use rethink. Rethink for the win. Super clear l. I had it running in minutes on my local machine and I believe it’s supposed to scale easy. Mongo wasn’t as easy and there free online db is so slow what’s the point. Very easy to find mongo code examples and use rethink code in its place. I wish I went this route years ago. All that corporate google Amazon crap get bent. The reason they have so much power in the world is cause you guys are giving it to them.

79.7k views79.7k
Comments
Karan
Karan

Senior Software Developer at Shyplite

Jan 13, 2022

Decided

So, we started using foundationDB for an OLAP system although the inbuilt tools for some core things like aggregation and filtering were negligible, with the high through put of the DB, we were able to handle it on the application. The system has been running pretty well for the past 6 months, although the data load isn’t very high yet, the performance is fairly promising

40.9k views40.9k
Comments

Detailed Comparison

CouchDB
CouchDB
ArangoDB
ArangoDB

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.

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.

Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync
multi-model nosql db; acid; transactions; javascript; database; nosql; sharding; replication; query language; joins; aql; documents; graphs; key-values; graphdb
Statistics
GitHub Stars
6.7K
GitHub Stars
-
GitHub Forks
1.1K
GitHub Forks
-
Stacks
529
Stacks
273
Followers
584
Followers
442
Votes
139
Votes
192
Pros & Cons
Pros
  • 43
    JSON
  • 30
    Open source
  • 18
    Highly available
  • 12
    Partition tolerant
  • 11
    Eventual consistency
Pros
  • 37
    Grahps and documents in one DB
  • 26
    Intuitive and rich query language
  • 25
    Open source
  • 25
    Good documentation
  • 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 CouchDB, ArangoDB?

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.

Memcached

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

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.

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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