DBMS > Neo4j vs. Netezza vs. Prometheus vs. RRDtool

System Properties Comparison Neo4j vs. Netezza vs. Prometheus vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

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

Data warehouse and analytics appliance part of IBM PureSystems

Open-source TimeSeries DBMS and monitoring system

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Graph DBMS

Relational DBMS

Time Series DBMS

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

Score	58.42
Rank	#19	Overall
	#1	Graph DBMS

Score	18.93
Rank	#38	Overall
	#24	Relational DBMS

Score	6.69
Rank	#63	Overall
	#3	Time Series DBMS

Score	2.40
Rank	#117	Overall
	#7	Time Series DBMS

Website

neo4j.com

www.ibm.com/products/netezza

prometheus.io

oss.oetiker.ch/rrdtool

Technical documentation

neo4j.com/docs

prometheus.io/docs

oss.oetiker.ch/rrdtool/doc

Developer

Neo4j, Inc.

IBM

Tobias Oetiker

Initial release

2007

2000

2015

1999

Current release

4.4.8, June 2022

1.7.2, May 2019

License

Commercial or Open Source

Open Source

GPL version3, commercial licenses available

commercial

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

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

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux

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

Linux

included in appliance

Linux
Windows

HP-UX
Linux

Data scheme

schema-free and schema-optional

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Exporting into and restoring from XML files possible

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

yes

APIs and other access methods

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

JDBC
ODBC
OLE DB

RESTful HTTP/JSON API

in-process shared library
Pipes

Supported programming languages

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

C
C++
Fortran
Java
Lua
Perl
Python
R

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

User defined Procedures and Functions

yes

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

yes using Neo4j Fabric

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Causal Clustering using Raft protocol

available in in Enterprise Version only

Source-replica replication

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

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

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

Competitive advantages

Neo4j is the market leader, graph database category creator, and the most widely...
» more

Typical application scenarios

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more

Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

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

News

Neo4j Ops Manager: One Place to Centrally and Easily Manage Neo4j Databases
29 June 2022

Neo4j Integrates Into Your Data Ecosystem with Connectors
29 June 2022

Developers.Zed: The LinkedIn for Developers in Zambia
27 June 2022

This Week in Neo4j: Bloom 2.3, Graph Data Science, Java, AWS, Python, Ontology, Microservices, and More
25 June 2022

Can’t Stop, Won’t Stop: Graph Data Science 2.1 Is Better Than Ever
23 June 2022

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