DBMS > Amazon Aurora vs. Apache Impala vs. Hypertable vs. Oracle vs. RDF4J

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Hypertable vs. Oracle vs. RDF4J

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Analytic DBMS for Hadoop

An open source BigTable implementation based on distributed file systems such as Hadoop

Widely used RDBMS

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

Primary database model

Secondary database models

Document store

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

aws.amazon.com/rds/aurora

impala.apache.org

www.oracle.com/database

rdf4j.org

Technical documentation

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

impala.apache.org/impala-docs.html

docs.oracle.com/en/database

rdf4j.org/documentation

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Hypertable Inc.

Oracle

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

Initial release

2015

2013

2009

1980

2004

Current release

4.1.0, June 2022

0.9.8.11, March 2016

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GNU version 3. Commercial license available

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Java

Server operating systems

hosted

Linux

Linux
OS X
Windows

an inofficial Windows port is available

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

yes

RDF Schemas

Typing

predefined data types such as float or date

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

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

C++ API
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

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

All languages supporting JDBC/ODBC

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

selectable replication factor on file system level

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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