DBMS > Amazon Redshift vs. MonetDB vs. Neo4j vs. TerminusDB vs. Warp 10

System Properties Comparison Amazon Redshift vs. MonetDB vs. Neo4j vs. TerminusDB vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A relational database management system that stores data in columns

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Graph DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Document store
RDF store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

www.monetdb.org/Documentation

neo4j.com/docs

terminusdb.github.io/terminusdb/#

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

MonetDB BV

Neo4j, Inc.

DataChemist Ltd.

SenX

Initial release

2012

2004

2007

2018

2015

Current release

Dec2023 (11.49), December 2023

5.20, May 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

GPL version3, commercial licenses available

Open Source

GPL V3

Open Source

Apache License 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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

Java, Scala

Prolog, Rust

Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free and schema-optional

yes

schema-free

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

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in SQL, C, R

yes

User defined Procedures and Functions

yes

WarpScript

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

yes using Neo4j Fabric

Graph Partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

Causal Clustering using Raft protocol

available in in Enterprise Version only

Journaling Streams

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

yes

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

in-memory journaling

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, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

Role-based access control

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
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