DBMS > ArangoDB vs. EsgynDB vs. Google BigQuery vs. Splice Machine vs. ToroDB

System Properties Comparison ArangoDB vs. EsgynDB vs. Google BigQuery vs. Splice Machine vs. ToroDB

Editorial information provided by DB-Engines

Name

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

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Large scale data warehouse service with append-only tables

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

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

Primary database model

Document store
Graph DBMS
Key-value store
Search engine

Relational 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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

arangodb.com

www.esgyn.cn

cloud.google.com/bigquery

splicemachine.com

github.com/torodb/server

Technical documentation

docs.arangodb.com

cloud.google.com/bigquery/docs

splicemachine.com/how-it-works

Social network pages

Developer

ArangoDB Inc.

Esgyn

Google

Splice Machine

8Kdata

Initial release

2012

2015

2010

2014

2016

Current release

3.11.5, November 2023

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial license (Enterprise) available

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

yes

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++, Java

Java

Server operating systems

Linux
OS X
Windows

Linux

hosted

Linux
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

schema-free

automatically recognizes schema within a collection

yes

schema-free

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

yes

string, integer, double, boolean, date, object_id

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

APIs and other access methods

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

ADO.NET
JDBC
ODBC

RESTful HTTP/JSON API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

JavaScript

Java Stored Procedures

user defined functions

in JavaScript

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with configurable replication factor

Multi-source replication between multi datacenters

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be done with stored procedures in JavaScript

yes

Yes, via Full Spark Integration

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

Eventual Consistency
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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

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

yes

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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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