DBMS > Amazon Aurora vs. atoti vs. Microsoft SQL Server vs. OrigoDB vs. Stardog

System Properties Comparison Amazon Aurora vs. atoti vs. Microsoft SQL Server vs. OrigoDB vs. Stardog

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Microsofts flagship relational DBMS

A fully ACID in-memory object graph database

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Object oriented DBMS

Relational DBMS

Document store
Object oriented DBMS

Graph DBMS
RDF store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

aws.amazon.com/rds/aurora

atoti.io

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

origodb.com

www.stardog.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.atoti.io

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

origodb.com/docs

docs.stardog.com

Developer

Amazon

ActiveViam

Microsoft

Robert Friberg et al

Stardog-Union

Initial release

2015

1989

2009

under the name LiveDB

2010

Current release

SQL Server 2022, November 2022

7.3.0, May 2020

License

Commercial or Open Source

commercial

free versions available

commercial

restricted free version is available

Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Java

Server operating systems

hosted

Linux
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

yes

can be achieved using .NET

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

Multidimensional Expressions (MDX)

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

ADO.NET
JDBC
ODBC

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

.NET Client API
HTTP API
LINQ

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

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

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

.Net

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

Python

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

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Domain Events

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding, horizontal partitioning

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

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

depending on model

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Write ahead log

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

fine grained access rights according to SQL-standard

Role based authorization

Access rights for users and roles

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