DBMS > IBM Db2 Event Store vs. Neo4j vs. RDFox vs. Snowflake vs. TerminusDB

System Properties Comparison IBM Db2 Event Store vs. Neo4j vs. RDFox vs. Snowflake vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

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

High performance knowledge graph and semantic reasoning engine

Cloud-based data warehousing service for structured and semi-structured data

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

Primary database model

Event Store
Time Series DBMS

Secondary database models

Relational DBMS

Document store
RDF store

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

www.ibm.com/products/db2-event-store

neo4j.com

www.oxfordsemantic.tech

www.snowflake.com

terminusdb.com

Technical documentation

www.ibm.com/docs/en/db2-event-store

neo4j.com/docs

docs.oxfordsemantic.tech

docs.snowflake.net/manuals/index.html

terminusdb.github.io/terminusdb/#

Developer

IBM

Neo4j, Inc.

Oxford Semantic Technologies

Snowflake Computing Inc.

DataChemist Ltd.

Initial release

2017

2007

2017

2014

2018

Current release

2.0

5.20, May 2024

6.0, Septermber 2022

11.0.0, January 2023

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL version3, commercial licenses available

commercial

Open Source

GPL V3

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

C and C++

Java, Scala

C++

Prolog, Rust

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux

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

Linux
macOS
Windows

hosted

Linux

Data scheme

yes

schema-free and schema-optional

yes

RDF schemas

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

RESTful HTTP API
SPARQL 1.1

CLI Client
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

C
Java

JavaScript (Node.js)
Python

JavaScript
Python

Server-side scripts

Stored procedures

yes

User defined Procedures and Functions

user defined functions

yes

Triggers

yes

via event handler

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes using Neo4j Fabric

yes

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

replication via a shared file system

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

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

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

in-memory journaling

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)

Roles, resources, and access types

Users with fine-grained authorization concept, user roles and pluggable authentication

Role-based access control

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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