DBMS > Amazon Redshift vs. Infobright vs. RDF4J vs. VictoriaMetrics

System Properties Comparison Amazon Redshift vs. Infobright vs. RDF4J vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Relational DBMS

RDF store

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

aws.amazon.com/redshift

ignitetech.com/softwarelibrary/infobrightdb

rdf4j.org

victoriametrics.com

Technical documentation

docs.aws.amazon.com/redshift

rdf4j.org/documentation

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Amazon (based on PostgreSQL)

Ignite Technologies Inc.; formerly InfoBright Inc.

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

VictoriaMetrics

Initial release

2012

2005

2004

2018

Current release

v1.91, May 2023

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

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0

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

Linux
OS X
Unix
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

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.

Secondary indexes

restricted

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

All languages supporting JDBC/ODBC

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

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

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

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

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