DBMS > ArangoDB vs. HEAVY.AI vs. Lovefield vs. VoltDB

System Properties Comparison ArangoDB vs. HEAVY.AI vs. Lovefield vs. VoltDB

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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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Graph DBMS
Key-value store
Search engine

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	3.26
Rank	#88	Overall
	#15	Document stores
	#5	Graph DBMS
	#12	Key-value stores
	#10	Search engines

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

arangodb.com

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

www.voltdb.com

Technical documentation

docs.arangodb.com

docs.heavy.ai

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

docs.voltdb.com

Social network pages

Developer

ArangoDB Inc.

HEAVY.AI, Inc.

Google

VoltDB Inc.

Initial release

2012

2016

2014

2010

Current release

3.11.5, November 2023

5.10, January 2022

2.1.12, February 2017

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial license (Enterprise) available

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

C++ and CUDA

JavaScript

Java, C++

Server operating systems

Linux
OS X
Windows

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X

for development

Data scheme

schema-free

automatically recognizes schema within a collection

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

yes

only a subset of SQL 99

APIs and other access methods

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

JDBC
ODBC
Thrift
Vega

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Java

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

Sharding

Round robin

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with configurable replication factor

Multi-source replication

none

Multi-source replication
Source-replica replication

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

Snapshots and command logging

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

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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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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