DBMS > Amazon Redshift vs. Informix vs. OrigoDB vs. RDFox vs. Teradata Aster

System Properties Comparison Amazon Redshift vs. Informix vs. OrigoDB vs. RDFox vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

A fully ACID in-memory object graph database

High performance knowledge graph and semantic reasoning engine

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Document store
Object oriented DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Website

aws.amazon.com/redshift

www.ibm.com/products/informix

origodb.com

www.oxfordsemantic.tech

Technical documentation

docs.aws.amazon.com/redshift

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

origodb.com/docs

docs.oxfordsemantic.tech

Developer

Amazon (based on PostgreSQL)

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Robert Friberg et al

Oxford Semantic Technologies

Teradata

Initial release

2012

1984

2009

under the name LiveDB

2017

2005

Current release

14.10.FC5, November 2020

6.0, Septermber 2022

License

Commercial or Open Source

commercial

free developer edition available

Open Source

commercial

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

C, C++ and Java

C++

Server operating systems

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
Windows

Linux
macOS
Windows

Linux

Data scheme

yes

RDF schemas

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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.

can be achieved using .NET

yes

in Aster File Store

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

.NET Client API
HTTP API
LINQ

RESTful HTTP API
SPARQL 1.1

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net

C
Java

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

yes

R packages

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

replication via a shared file system

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

depending on model

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

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

Users with fine-grained authentication, authorization, and auditing controls

Role based authorization

Roles, resources, and access types

fine grained access rights according to SQL-standard

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