DBMS > ArcadeDB vs. CouchDB vs. ToroDB vs. Vitess

System Properties Comparison ArcadeDB vs. CouchDB vs. ToroDB vs. Vitess

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

arcadedb.com

couchdb.apache.org

github.com/torodb/server

vitess.io

Technical documentation

docs.arcadedb.com

docs.couchdb.org/en/stable

vitess.io/docs

Developer

Arcade Data

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

8Kdata

The Linux Foundation, PlanetScale

Initial release

2021

2005

2016

2013

Current release

September 2021

3.3.3, December 2023

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

AGPL-V3

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

Java

Server operating systems

All OS with a Java VM

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java 7 VM

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

with proprietary extensions

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

RESTful HTTP/JSON API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Java

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

View functions in JavaScript

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

relationship in graphs

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

atomic operations within a single document possible

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users can be defined per database

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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More resources

DB-Engines blog posts

Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month
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Recent citations in the news

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16 June 2022, TechRepublic

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15 March 2022, The Register

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27 February 2020, DevClass

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28 August 2014, SitePoint

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18 May 2021, Datanami

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13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News

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