DBMS > Amazon Redshift vs. OpenQM vs. Postgres-XL vs. Splunk

System Properties Comparison Amazon Redshift vs. OpenQM vs. Postgres-XL vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

QpenQM is a high-performance, self-tuning, multi-value DBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Analytics Platform for Big Data

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

aws.amazon.com/redshift

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.postgres-xl.org

www.splunk.com

Technical documentation

docs.aws.amazon.com/redshift

www.postgres-xl.org/documentation

docs.splunk.com/Documentation/Splunk

Developer

Amazon (based on PostgreSQL)

Rocket Software, originally Martin Phillips

Splunk Inc.

Initial release

2012

1993

2014

since 2012, originally named StormDB

2003

Current release

3.4-12

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Mozilla public license

commercial

Limited free edition and free developer edition available

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

Server operating systems

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
macOS

Linux
OS X
Solaris
Windows

Data scheme

yes

with some exceptions

yes

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

XML type, but no XML query functionality

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

distributed, parallel query execution

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

Transaction concepts

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

ACID

MVCC

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights for users and roles

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