DBMS > ArangoDB vs. EsgynDB vs. Microsoft SQL Server vs. Quasardb

System Properties Comparison ArangoDB vs. EsgynDB vs. Microsoft SQL Server vs. Quasardb

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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.

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

Microsofts flagship relational DBMS

Distributed, high-performance timeseries database

Primary database model

Document store
Graph DBMS
Key-value store
Search engine

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

arangodb.com

www.esgyn.cn

www.microsoft.com/en-us/sql-server

quasar.ai

Technical documentation

docs.arangodb.com

learn.microsoft.com/en-US/sql/sql-server

doc.quasar.ai/master

Social network pages

Developer

ArangoDB Inc.

Esgyn

Microsoft

quasardb

Initial release

2012

2015

1989

2009

Current release

3.11.5, November 2023

SQL Server 2022, November 2022

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial license (Enterprise) available

commercial

restricted free version is available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++, Java

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

BSD
Linux
OS X
Windows

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

integer and binary

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.

yes

Secondary indexes

yes

with tags

SQL

Support of SQL

yes

SQL-like query language

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

JavaScript

Java Stored Procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with configurable replication factor

Multi-source replication between multi datacenters

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

can be done with stored procedures in JavaScript

yes

with Hadoop 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

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

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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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