DBMS > Amazon Neptune vs. ArcadeDB vs. Fauna vs. Microsoft SQL Server vs. SiriDB

System Properties Comparison Amazon Neptune vs. ArcadeDB vs. Fauna vs. Microsoft SQL Server vs. SiriDB

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Microsofts flagship relational DBMS

Open Source Time Series DBMS

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

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	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/neptune

arcadedb.com

fauna.com

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

siridb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.arcadedb.com

docs.fauna.com

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

docs.siridb.com

Developer

Amazon

Arcade Data

Fauna, Inc.

Microsoft

Cesbit

Initial release

2017

2021

2014

1989

2017

Current release

September 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

Scala

C++

Server operating systems

hosted

All OS with a Java VM

hosted

Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

SQL

Support of SQL

SQL-like query language, no joins

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

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

RESTful HTTP API

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

HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Java

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

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

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

consistent hashing

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Source-replica replication

Multi-source replication

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationship 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

with encyption-at-rest

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 and roles can be defined via the AWS Identity and Access Management (IAM)

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

simple rights management via user accounts

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