DBMS > ArangoDB vs. DataFS vs. Dolt vs. Lovefield

System Properties Comparison ArangoDB vs. DataFS vs. Dolt vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

A MySQL compatible DBMS with Git-like versioning of data and schema

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Document store
Graph DBMS
Key-value store
Search engine

Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS

Document store

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

Score	3.32
Rank	#90	Overall
	#15	Document stores
	#5	Graph DBMS
	#12	Key-value stores
	#10	Search engines

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

arangodb.com

newdatabase.com

github.com/dolthub/dolt
www.dolthub.com

google.github.io/lovefield

Technical documentation

docs.arangodb.com

dev.mobiland.com/Overview.xsp

docs.dolthub.com

github.com/google/lovefield/blob/master/docs/spec_index.md

Social network pages

Developer

ArangoDB Inc.

Mobiland AG

DoltHub Inc

Google

Initial release

2012

2018

2014

Current release

3.11.5, November 2023

1.1.263, October 2022

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial license (Enterprise) available

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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.

ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.

Implementation language

C++

JavaScript

Server operating systems

Linux
OS X
Windows

Windows

Linux
macOS
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

schema-free

automatically recognizes schema within a collection

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

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

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream

.NET Client API
Proprietary client DLL
WinRT client

CLI Client
HTTP REST

Supported programming languages

C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust

.Net
C
C#
C++
VB.Net

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

JavaScript

Server-side scripts

Stored procedures

JavaScript

yes

currently in alpha release

Triggers

no, except callback-events from server when changes happened

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

Proprietary Sharding system

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with configurable replication factor

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be done with stored procedures in JavaScript

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

configurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

yes

Windows-Profile

Only one user is configurable, and must be specified in the config file at startup

More information provided by the system vendor

Specific characteristics

Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more

Competitive advantages

Consolidation: As a native multi-model database, can be used as a full blown document...
» more

Typical application scenarios

Native multi-model in ArangoDB is being used for a broad range of projects across...
» more

Key customers

Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more

Market metrics

ArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more

Licensing and pricing models

Very permissive Apache 2 License for Community Edition & commercial licenses are...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

The Weight of Relational Databases: Time for Multi-Model?
29 August 2017, Luca Olivari (guest author)

show all

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