DBMS > Amazon Redshift vs. Graph Engine vs. MonetDB vs. Splunk

System Properties Comparison Amazon Redshift vs. Graph Engine vs. MonetDB 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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A relational database management system that stores data in columns

Analytics Platform for Big Data

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Search engine

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	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

aws.amazon.com/redshift

www.graphengine.io

www.monetdb.org

www.splunk.com

Technical documentation

docs.aws.amazon.com/redshift

www.graphengine.io/docs/manual

www.monetdb.org/Documentation

docs.splunk.com/Documentation/Splunk

Developer

Amazon (based on PostgreSQL)

Microsoft

MonetDB BV

Splunk Inc.

Initial release

2012

2010

2004

2003

Current release

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Mozilla Public License 2.0

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

.NET and C

Server operating systems

hosted

.NET

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

yes, in SQL, C, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

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

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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 for users and roles

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