DBMS > Amazon Aurora vs. Infobright vs. OrientDB vs. RDF4J vs. SQLite

System Properties Comparison Amazon Aurora vs. Infobright vs. OrientDB vs. RDF4J vs. SQLite

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Multi-model DBMS (Document, Graph, Key/Value)

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

RDF store

Relational DBMS

Secondary database models

Document store

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/rds/aurora

ignitetech.com/softwarelibrary/infobrightdb

orientdb.org

rdf4j.org

www.sqlite.org

Technical documentation

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

www.orientdb.com/docs/last/index.html

rdf4j.org/documentation

www.sqlite.org/docs.html

Developer

Amazon

Ignite Technologies Inc.; formerly InfoBright Inc.

OrientDB LTD; CallidusCloud; SAP

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Dwayne Richard Hipp

Initial release

2015

2005

2010

2004

2000

Current release

3.2.29, March 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Apache version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Public Domain

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.

Implementation language

Java

Server operating systems

hosted

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Linux
OS X
Unix
Windows

server-less

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

RDF Schemas

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL-like query language, no joins

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Java, Javascript

yes

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users and roles; record level security configurable

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